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100 Great Computer Science Research Topics Ideas for 2023

Being a computer student in 2023 is not easy. Besides studying a constantly evolving subject, you have to come up with great computer science research topics at some point in your academic life. If you’re reading this article, you’re among many other students that have also come to this realization.

Interesting Computer Science Topics

Awesome research topics in computer science, hot topics in computer science, topics to publish a journal on computer science.

• Controversial Topics in Computer Science

Fun AP Computer Science Topics

Exciting computer science ph.d. topics, remarkable computer science research topics for undergraduates, incredible final year computer science project topics, advanced computer science topics, unique seminars topics for computer science, exceptional computer science masters thesis topics, outstanding computer science presentation topics.

• Key Computer Science Essay Topics

Main Project Topics for Computer Science

• We Can Help You with Computer Science Topics

Whether you’re earnestly searching for a topic or stumbled onto this article by accident, there is no doubt that every student needs excellent computer science-related topics for their paper. A good topic will not only give your essay or research a good direction but will also make it easy to come up with supporting points. Your topic should show all your strengths as well.

Fortunately, this article is for every student that finds it hard to generate a suitable computer science topic. The following 100+ topics will help give you some inspiration when creating your topics. Let’s get into it.

One of the best ways of making your research paper interesting is by coming up with relevant topics in computer science . Here are some topics that will make your paper immersive:

• Evolution of virtual reality
• What is green cloud computing
• Ways of creating a Hopefield neural network in C++
• Developments in graphic systems in computers
• The five principal fields in robotics
• Developments and applications of nanotechnology
• Differences between computer science and applied computing

Your next research topic in computer science shouldn’t be tough to find once you’ve read this section. If you’re looking for simple final year project topics in computer science, you can find some below.

• Applications of the blockchain technology in the banking industry
• Computational thinking and how it influences science
• Ways of terminating phishing
• Uses of artificial intelligence in cyber security
• Define the concepts of a smart city
• Applications of the Internet of Things
• Discuss the applications of the face detection application

Whenever a topic is described as “hot,” it means that it is a trendy topic in computer science. If computer science project topics for your final years are what you’re looking for, have a look at some below:

• Applications of the Metaverse in the world today
• Discuss the challenges of machine learning
• Advantages of artificial intelligence
• Applications of nanotechnology in the paints industry
• What is quantum computing?
• Discuss the languages of parallel computing
• What are the applications of computer-assisted studies?

Perhaps you’d like to write a paper that will get published in a journal. If you’re searching for the best project topics for computer science students that will stand out in a journal, check below:

• Developments in human-computer interaction
• Applications of computer science in medicine
• Developments in artificial intelligence in image processing
• Discuss cryptography and its applications
• Discuss methods of ransomware prevention
• Applications of Big Data in the banking industry
• Challenges of cloud storage services in 2023

 Controversial Topics in Computer Science

Some of the best computer science final year project topics are those that elicit debates or require you to take a stand. You can find such topics listed below for your inspiration:

• Can robots be too intelligent?
• Should the dark web be shut down?
• Should your data be sold to corporations?
• Will robots completely replace the human workforce one day?
• How safe is the Metaverse for children?
• Will artificial intelligence replace actors in Hollywood?
• Are social media platforms safe anymore?

Are you a computer science student looking for AP topics? You’re in luck because the following final year project topics for computer science are suitable for you.

• Standard browser core with CSS support
• Applications of the Gaussian method in C++ development in integrating functions
• Vital conditions of reducing risk through the Newton method
• How to reinforce machine learning algorithms.
• How do artificial neural networks function?
• Discuss the advancements in computer languages in machine learning
• Use of artificial intelligence in automated cars

When studying to get your doctorate in computer science, you need clear and relevant topics that generate the reader’s interest. Here are some Ph.D. topics in computer science you might consider:

• Developments in information technology
• Is machine learning detrimental to the human workforce?
• How to write an algorithm for deep learning
• What is the future of 5G in wireless networks
• Statistical data in Maths modules in Python
• Data retention automation from a website using API
• Application of modern programming languages

Looking for computer science topics for research is not easy for an undergraduate. Fortunately, these computer science project topics should make your research paper easy:

• Ways of using artificial intelligence in real estate
• Discuss reinforcement learning and its applications
• Uses of Big Data in science and medicine
• How to sort algorithms using Haskell
• How to create 3D configurations for a website
• Using inverse interpolation to solve non-linear equations
• Explain the similarities between the Internet of Things and artificial intelligence

Your dissertation paper is one of the most crucial papers you’ll ever do in your final year. That’s why selecting the best ethics in computer science topics is a crucial part of your paper. Here are some project topics for the computer science final year.

• How to incorporate numerical methods in programming
• Applications of blockchain technology in cloud storage
• How to come up with an automated attendance system
• Using dynamic libraries for site development
• How to create cubic splines
• Applications of artificial intelligence in the stock market
• Uses of quantum computing in financial modeling

Your instructor may want you to challenge yourself with an advanced science project. Thus, you may require computer science topics to learn and research. Here are some that may inspire you:

• Discuss the best cryptographic protocols
• Advancement of artificial intelligence used in smartphones
• Briefly discuss the types of security software available
• Application of liquid robots in 2023
• How to use quantum computers to solve decoherence problem
• macOS vs. Windows; discuss their similarities and differences
• Explain the steps taken in a cyber security audit

When searching for computer science topics for a seminar, make sure they are based on current research or events. Below are some of the latest research topics in computer science:

• How to reduce cyber-attacks in 2023
• Steps followed in creating a network
• Discuss the uses of data science
• Discuss ways in which social robots improve human interactions
• Differentiate between supervised and unsupervised machine learning
• Applications of robotics in space exploration
• The contrast between cyber-physical and sensor network systems

Are you looking for computer science thesis topics for your upcoming projects? The topics below are meant to help you write your best paper yet:

• Applications of computer science in sports
• Uses of computer technology in the electoral process
• Using Fibonacci to solve the functions maximum and their implementations
• Discuss the advantages of using open-source software
• Expound on the advancement of computer graphics
• Briefly discuss the uses of mesh generation in computational domains
• How much data is generated from the internet of things?

A computer science presentation requires a topic relevant to current events. Whether your paper is an assignment or a dissertation, you can find your final year computer science project topics below:

• Uses of adaptive learning in the financial industry
• Applications of transitive closure on graph
• Using RAD technology in developing software
• Discuss how to create maximum flow in the network
• How to design and implement functional mapping
• Using artificial intelligence in courier tracking and deliveries
• How to make an e-authentication system

 Key Computer Science Essay Topics

You may be pressed for time and require computer science master thesis topics that are easy. Below are some topics that fit this description:

• What are the uses of cloud computing in 2023
• Discuss the server-side web technologies
• Compare and contrast android and iOS
• How to come up with a face detection algorithm
• What is the future of NFTs
• How to create an artificial intelligence shopping system
• How to make a software piracy prevention algorithm

One major mistake students make when writing their papers is selecting topics unrelated to the study at hand. This, however, will not be an issue if you get topics related to computer science, such as the ones below:

• Using blockchain to create a supply chain management system
• How to protect a web app from malicious attacks
• Uses of distributed information processing systems
• Advancement of crowd communication software since COVID-19
• Uses of artificial intelligence in online casinos
• Discuss the pillars of math computations
• Discuss the ethical concerns arising from data mining

We Can Help You with Computer Science Topics, Essays, Thesis, and Research Papers

We hope that this list of computer science topics helps you out of your sticky situation. We do offer other topics in different subjects. Additionally, we also offer professional writing services tailor-made for you.

We understand what students go through when searching the internet for computer science research paper topics, and we know that many students don’t know how to write a research paper to perfection. However, you shouldn’t have to go through all this when we’re here to help.

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How to Contact Faculty for IW/Thesis Advising

Send the professor an e-mail. When you write a professor, be clear that you want a meeting regarding a senior thesis or one-on-one IW project, and briefly describe the topic or idea that you want to work on. Check the faculty listing for email addresses.

Parastoo Abtahi, Room 419

Available for single-semester IW and senior thesis advising, 2023-2024

• Research Areas: Human-Computer Interaction (HCI), Augmented Reality (AR), and Spatial Computing
• Input techniques for on-the-go interaction (e.g., eye-gaze, microgestures, voice) with a focus on uncertainty, disambiguation, and privacy.
• Minimal and timely multisensory output (e.g., spatial audio, haptics) that enables users to attend to their physical environment and the people around them, instead of a 2D screen.
• Interaction with intelligent systems (e.g., IoT, robots) situated in physical spaces with a focus on updating users’ mental model despite the complexity and dynamicity of these systems.

Ryan Adams, Room 411

Research areas:

• Machine learning driven design
• Generative models for structured discrete objects
• Approximate inference in probabilistic models
• Accelerating solutions to partial differential equations
• Innovative uses of automatic differentiation
• Modeling and optimizing 3d printing and CNC machining

Andrew Appel, Room 209

• Research Areas: Formal methods, programming languages, compilers, computer security.
• Software verification (for which taking COS 326 / COS 510 is helpful preparation)
• Game theory of poker or other games (for which COS 217 / 226 are helpful)
• Computer game-playing programs (for which COS 217 / 226)
•  Risk-limiting audits of elections (for which ORF 245 or other knowledge of probability is useful)

Sanjeev Arora, Room 407

• Theoretical machine learning, deep learning and its analysis, natural language processing. My advisees would typically have taken a course in algorithms (COS423 or COS 521 or equivalent) and a course in machine learning.
• Show that finding approximate solutions to NP-complete problems is also NP-complete (i.e., come up with NP-completeness reductions a la COS 487). 
• Experimental Algorithms: Implementing and Evaluating Algorithms using existing software packages. 
• Studying/designing provable algorithms for machine learning and implementions using packages like scipy and MATLAB, including applications in Natural language processing and deep learning.
• Any topic in theoretical computer science.

David August, Room 221

• Research Areas: Computer Architecture, Compilers, Parallelism
• Containment-based approaches to security:  We have designed and tested a simple hardware+software containment mechanism that stops incorrect communication resulting from faults, bugs, or exploits from leaving the system.   Let's explore ways to use containment to solve real problems.  Expect to work with corporate security and technology decision-makers.
• Parallelism: Studies show much more parallelism than is currently realized in compilers and architectures.  Let's find ways to realize this parallelism.
• Any other interesting topic in computer architecture or compilers. 

Mark Braverman, 194 Nassau St., Room 231

Available for Spring 2024 single-semester IW, only

• Research Areas: computational complexity, algorithms, applied probability, computability over the real numbers, game theory and mechanism design, information theory.
• Topics in computational and communication complexity.
• Applications of information theory in complexity theory.
• Algorithms for problems under real-life assumptions.
• Game theory, network effects
• Mechanism design (could be on a problem proposed by the student)

Sebastian Caldas, 221 Nassau Street, Room 105

• Research Areas: collaborative learning, machine learning for healthcare. Typically, I will work with students that have taken COS324.
• Methods for collaborative and continual learning.
• Machine learning for healthcare applications.

Bernard Chazelle, 194 Nassau St., Room 301

• Research Areas: Natural Algorithms, Computational Geometry, Sublinear Algorithms. 
• Natural algorithms (flocking, swarming, social networks, etc).
• Sublinear algorithms
• Self-improving algorithms
• Markov data structures

Danqi Chen, Room 412

Not available for IW or thesis advising, 2023-2024

• My advisees would be expected to have taken a course in machine learning and ideally have taken COS484 or an NLP graduate seminar.
• Representation learning for text and knowledge bases
• Pre-training and transfer learning
• Question answering and reading comprehension
• Information extraction
• Text summarization
• Any other interesting topics related to natural language understanding/generation

Marcel Dall'Agnol, Corwin 034

Available for single-semester and senior thesis advising, 2023-2024

• Research Areas: Theoretical computer science. (Specifically, quantum computation, sublinear algorithms, complexity theory, interactive proofs and cryptography)

Jia Deng, Room 423

Available for Fall 2023 single-semester IW, only

•  Research Areas: Computer Vision, Machine Learning.
• Object recognition and action recognition
• Deep Learning, autoML, meta-learning
• Geometric reasoning, logical reasoning

Adji Bousso Dieng, Room 406

• Research areas: Vertaix is a research lab at Princeton University led by Professor Adji Bousso Dieng. We work at the intersection of artificial intelligence (AI) and the natural sciences. The models and algorithms we develop are motivated by problems in those domains and contribute to advancing methodological research in AI. We leverage tools in statistical machine learning and deep learning in developing methods for learning with the data, of various modalities, arising from the natural sciences.

Robert Dondero, Corwin Hall, Room 038

• Research Areas:  Software engineering; software engineering education.
• Develop or evaluate tools to facilitate student learning in undergraduate computer science courses at Princeton, and beyond.
• In particular, can code critiquing tools help students learn about software quality?

Zeev Dvir, 194 Nassau St., Room 250

Not available for IW or thesis advising, 2023-2024.

• Research Areas: computational complexity, pseudo-randomness, coding theory and discrete mathematics.
• Independent Research: I have various research problems related to Pseudorandomness, Coding theory, Complexity and Discrete mathematics - all of which require strong mathematical background. A project could also be based on writing a survey paper describing results from a few theory papers revolving around some particular subject.

Benjamin Eysenbach, Room 416

• Research areas: reinforcement learning, machine learning. My advisees would typically have taken COS324.
• Using RL algorithms to applications in science and engineering.
• Emergent behavior of RL algorithms on high-fidelity robotic simulators.
• Studying how architectures and representations can facilitate generalization.

Christiane Fellbaum, 1-S-14 Green

No longer available for single-term IW and senior thesis advising, 2023-2024

• Research Areas: theoretical and computational linguistics, word sense disambiguation, lexical resource construction, English and multilingual WordNet(s), ontology
• Anything having to do with natural language--come and see me with/for ideas suitable to your background and interests. Some topics students have worked on in the past:
• Developing parsers, part-of-speech taggers, morphological analyzers for underrepresented languages (you don't have to know the language to develop such tools!)
• Quantitative approaches to theoretical linguistics questions
• Extensions and interfaces for WordNet (English and WN in other languages),
• Applications of WordNet(s), including:
• Foreign language tutoring systems,
• Spelling correction software,
• Word-finding/suggestion software for ordinary users and people with memory problems,
• Machine Translation 
• Sentiment and Opinion detection
• Automatic reasoning and inferencing
• Collaboration with professors in the social sciences and humanities ("Digital Humanities")

Adam Finkelstein, Room 424 

• Research Areas: computer graphics, audio.

Robert S. Fish, Corwin Hall, Room 037

No longer available for single-semester IW and senior thesis advising, 2023-2024

• Networking and telecommunications
• Learning, perception, and intelligence, artificial and otherwise;
• Human-computer interaction and computer-supported cooperative work
• Online education, especially in Computer Science Education
• Topics in research and development innovation methodologies including standards, open-source, and entrepreneurship
• Distributed autonomous organizations and related blockchain technologies

Michael Freedman, Room 308 

• Research Areas: Distributed systems, security, networking
• Projects related to streaming data analysis, datacenter systems and networks, untrusted cloud storage and applications. Please see my group website at http://sns.cs.princeton.edu/ for current research projects.

Ruth Fong, Room 032

• Research Areas: computer vision, machine learning, deep learning, interpretability, explainable AI, fairness and bias in AI
• Develop a technique for understanding AI models
• Design a AI model that is interpretable by design
• Build a paradigm for detecting and/or correcting failure points in an AI model
• Analyze an existing AI model and/or dataset to better understand its failure points
• Build a computer vision system for another domain (e.g., medical imaging, satellite data, etc.)
• Develop a software package for explainable AI
• Adapt explainable AI research to a consumer-facing problem

Note: I am happy to advise any project if there's a sufficient overlap in interest and/or expertise; please reach out via email to chat about project ideas.

Tom Griffiths, Room 405

Research areas: computational cognitive science, computational social science, machine learning and artificial intelligence

Note: I am open to projects that apply ideas from computer science to understanding aspects of human cognition in a wide range of areas, from decision-making to cultural evolution and everything in between. For example, we have current projects analyzing chess game data and magic tricks, both of which give us clues about how human minds work. Students who have expertise or access to data related to games, magic, strategic sports like fencing, or other quantifiable domains of human behavior feel free to get in touch.

Aarti Gupta, Room 220

• Research Areas: Formal methods, program analysis, logic decision procedures
• Finding bugs in open source software using automatic verification tools
• Software verification (program analysis, model checking, test generation)
• Decision procedures for logical reasoning (SAT solvers, SMT solvers)

Elad Hazan, Room 409  

• Research interests: machine learning methods and algorithms, efficient methods for mathematical optimization, regret minimization in games, reinforcement learning, control theory and practice
• Machine learning, efficient methods for mathematical optimization, statistical and computational learning theory, regret minimization in games.
• Implementation and algorithm engineering for control, reinforcement learning and robotics
• Implementation and algorithm engineering for time series prediction

Felix Heide, Room 410

• Research Areas: Computational Imaging, Computer Vision, Machine Learning (focus on Optimization and Approximate Inference).
• Optical Neural Networks
• Hardware-in-the-loop Holography
• Zero-shot and Simulation-only Learning
• Object recognition in extreme conditions
• 3D Scene Representations for View Generation and Inverse Problems
• Long-range Imaging in Scattering Media
• Hardware-in-the-loop Illumination and Sensor Optimization
• Inverse Lidar Design
• Phase Retrieval Algorithms
• Proximal Algorithms for Learning and Inference
• Domain-Specific Language for Optics Design

Kyle Jamieson, Room 306

• Research areas: Wireless and mobile networking; indoor radar and indoor localization; Internet of Things
• See other topics on my independent work  ideas page  (campus IP and CS dept. login req'd)

Alan Kaplan, 221 Nassau Street, Room 105

Research Areas:

• Random apps of kindness - mobile application/technology frameworks used to help individuals or communities; topic areas include, but are not limited to: first response, accessibility, environment, sustainability, social activism, civic computing, tele-health, remote learning, crowdsourcing, etc.
• Tools automating programming language interoperability - Java/C++, React Native/Java, etc.
• Software visualization tools for education
• Connected consumer devices, applications and protocols

Brian Kernighan, Room 311

• Research Areas: application-specific languages, document preparation, user interfaces, software tools, programming methodology
• Application-oriented languages, scripting languages.
• Tools; user interfaces
• Digital humanities

Zachary Kincaid, Room 219

• Research areas: programming languages, program analysis, program verification, automated reasoning
• Independent Research Topics:
• Develop a practical algorithm for an intractable problem (e.g., by developing practical search heuristics, or by reducing to, or by identifying a tractable sub-problem, ...).
• Design a domain-specific programming language, or prototype a new feature for an existing language.
• Any interesting project related to programming languages or logic.

Gillat Kol, Room 316

Aleksandra korolova, 309 sherrerd hall.

Available for single-term IW and senior thesis advising, 2023-2024

• Research areas: Societal impacts of algorithms and AI; privacy; fair and privacy-preserving machine learning; algorithm auditing.

Advisees typically have taken one or more of COS 226, COS 324, COS 423, COS 424 or COS 445.

Amit Levy, Room 307

• Research Areas: Operating Systems, Distributed Systems, Embedded Systems, Internet of Things
• Distributed hardware testing infrastructure
• Second factor security tokens
• Low-power wireless network protocol implementation
• USB device driver implementation

Kai Li, Room 321

• Research Areas: Distributed systems; storage systems; content-based search and data analysis of large datasets.
• Fast communication mechanisms for heterogeneous clusters.
• Approximate nearest-neighbor search for high dimensional data.
• Data analysis and prediction of in-patient medical data.
• Optimized implementation of classification algorithms on manycore processors.

Xiaoyan Li, 221 Nassau Street, Room 104

• Research areas: Information retrieval, novelty detection, question answering, AI, machine learning and data analysis.
• Explore new statistical retrieval models for document retrieval and question answering.
• Apply AI in various fields.
• Apply supervised or unsupervised learning in health, education, finance, and social networks, etc.
• Any interesting project related to AI, machine learning, and data analysis.

Wyatt Lloyd, Room 323

• Research areas: Distributed Systems
• Caching algorithms and implementations
• Storage systems
• Distributed transaction algorithms and implementations

Margaret Martonosi, Room 208

• Quantum Computing research, particularly related to architecture and compiler issues for QC.
• Computer architectures specialized for modern workloads (e.g., graph analytics, machine learning algorithms, mobile applications
• Investigating security and privacy vulnerabilities in computer systems, particularly IoT devices.
• Other topics in computer architecture or mobile / IoT systems also possible.

Jonathan Mayer, Sherrerd Hall, Room 307 

• Research areas: Technology law and policy, with emphasis on national security, criminal procedure, consumer privacy, network management, and online speech.
• Assessing the effects of government policies, both in the public and private sectors.
• Collecting new data that relates to government decision making, including surveying current business practices and studying user behavior.
• Developing new tools to improve government processes and offer policy alternatives.

Andrés Monroy-Hernández, Room 405

• Research Areas: Human-Computer Interaction, Social Computing, Public-Interest Technology, Augmented Reality, Urban Computing
• Research interests:developing public-interest socio-technical systems.  We are currently creating alternatives to gig work platforms that are more equitable for all stakeholders. For instance, we are investigating the socio-technical affordances necessary to support a co-op food delivery network owned and managed by workers and restaurants. We are exploring novel system designs that support self-governance, decentralized/federated models, community-centered data ownership, and portable reputation systems.  We have opportunities for students interested in human-centered computing, UI/UX design, full-stack software development, and qualitative/quantitative user research.
• Beyond our core projects, we are open to working on research projects that explore the use of emerging technologies, such as AR, wearables, NFTs, and DAOs, for creative and out-of-the-box applications.

Christopher Moretti, Corwin Hall, Room 036

• Research areas: Distributed systems, high-throughput computing, computer science/engineering education
• Expansion, improvement, and evaluation of open-source distributed computing software.
• Applications of distributed computing for "big science" (e.g. biometrics, data mining, bioinformatics)
• Software and best practices for computer science education and study, especially Princeton's 126/217/226 sequence or MOOCs development
• Sports analytics and/or crowd-sourced computing

Radhika Nagpal, F316 Engineering Quadrangle

• Research areas: control, robotics and dynamical systems

Karthik Narasimhan, Room 422

• Research areas: Natural Language Processing, Reinforcement Learning
• Autonomous agents for text-based games ( https://www.microsoft.com/en-us/research/project/textworld/ )
• Transfer learning/generalization in NLP
• Techniques for generating natural language
• Model-based reinforcement learning

Arvind Narayanan, 308 Sherrerd Hall 

Research Areas: fair machine learning (and AI ethics more broadly), the social impact of algorithmic systems, tech policy

Pedro Paredes, Corwin Hall, Room 041

My primary research work is in Theoretical Computer Science.

 * Research Interest: Spectral Graph theory, Pseudorandomness, Complexity theory, Coding Theory, Quantum Information Theory, Combinatorics.

The IW projects I am interested in advising can be divided into three categories:

 1. Theoretical research

I am open to advise work on research projects in any topic in one of my research areas of interest. A project could also be based on writing a survey given results from a few papers. Students should have a solid background in math (e.g., elementary combinatorics, graph theory, discrete probability, basic algebra/calculus) and theoretical computer science (226 and 240 material, like big-O/Omega/Theta, basic complexity theory, basic fundamental algorithms). Mathematical maturity is a must.

A (non exhaustive) list of topics of projects I'm interested in:   * Explicit constructions of better vertex expanders and/or unique neighbor expanders.   * Construction deterministic or random high dimensional expanders.   * Pseudorandom generators for different problems.   * Topics around the quantum PCP conjecture.   * Topics around quantum error correcting codes and locally testable codes, including constructions, encoding and decoding algorithms.

 2. Theory informed practical implementations of algorithms   Very often the great advances in theoretical research are either not tested in practice or not even feasible to be implemented in practice. Thus, I am interested in any project that consists in trying to make theoretical ideas applicable in practice. This includes coming up with new algorithms that trade some theoretical guarantees for feasible implementation yet trying to retain the soul of the original idea; implementing new algorithms in a suitable programming language; and empirically testing practical implementations and comparing them with benchmarks / theoretical expectations. A project in this area doesn't have to be in my main areas of research, any theoretical result could be suitable for such a project.

Some examples of areas of interest:   * Streaming algorithms.   * Numeric linear algebra.   * Property testing.   * Parallel / Distributed algorithms.   * Online algorithms.    3. Machine learning with a theoretical foundation

I am interested in projects in machine learning that have some mathematical/theoretical, even if most of the project is applied. This includes topics like mathematical optimization, statistical learning, fairness and privacy.

One particular area I have been recently interested in is in the area of rating systems (e.g., Chess elo) and applications of this to experts problems.

Final Note: I am also willing to advise any project with any mathematical/theoretical component, even if it's not the main one; please reach out via email to chat about project ideas.

Iasonas Petras, Corwin Hall, Room 033

• Research Areas: Information Based Complexity, Numerical Analysis, Quantum Computation.
• Prerequisites: Reasonable mathematical maturity. In case of a project related to Quantum Computation a certain familiarity with quantum mechanics is required (related courses: ELE 396/PHY 208).
• Possible research topics include:

1.   Quantum algorithms and circuits:

• i. Design or simulation quantum circuits implementing quantum algorithms.
• ii. Design of quantum algorithms solving/approximating continuous problems (such as Eigenvalue problems for Partial Differential Equations).

2.   Information Based Complexity:

• i. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems in various settings (for example worst case or average case). 
• ii. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems under new tractability and error criteria.
• iii. Necessary and sufficient conditions for tractability of Weighted problems.
• iv. Necessary and sufficient conditions for tractability of Weighted Problems under new tractability and error criteria.

3. Topics in Scientific Computation:

• i. Randomness, Pseudorandomness, MC and QMC methods and their applications (Finance, etc)

Yuri Pritykin, 245 Carl Icahn Lab

• Research interests: Computational biology; Cancer immunology; Regulation of gene expression; Functional genomics; Single-cell technologies.
• Potential research projects: Development, implementation, assessment and/or application of algorithms for analysis, integration, interpretation and visualization of multi-dimensional data in molecular biology, particularly single-cell and spatial genomics data.

Benjamin Raphael, Room 309  

• Research interests: Computational biology and bioinformatics; Cancer genomics; Algorithms and machine learning approaches for analysis of large-scale datasets
• Implementation and application of algorithms to infer evolutionary processes in cancer
• Identifying correlations between combinations of genomic mutations in human and cancer genomes
• Design and implementation of algorithms for genome sequencing from new DNA sequencing technologies
• Graph clustering and network anomaly detection, particularly using diffusion processes and methods from spectral graph theory

Vikram Ramaswamy, 035 Corwin Hall

• Research areas: Interpretability of AI systems, Fairness in AI systems, Computer vision.
• Constructing a new method to explain a model / create an interpretable by design model
• Analyzing a current model / dataset to understand bias within the model/dataset
• Proposing new fairness evaluations
• Proposing new methods to train to improve fairness
• Developing synthetic datasets for fairness / interpretability benchmarks
• Understanding robustness of models

Ran Raz, Room 240

• Research Area: Computational Complexity
• Independent Research Topics: Computational Complexity, Information Theory, Quantum Computation, Theoretical Computer Science

Szymon Rusinkiewicz, Room 406

• Research Areas: computer graphics; computer vision; 3D scanning; 3D printing; robotics; documentation and visualization of cultural heritage artifacts
• Research ways of incorporating rotation invariance into computer visiontasks such as feature matching and classification
• Investigate approaches to robust 3D scan matching
• Model and compensate for imperfections in 3D printing
• Given a collection of small mobile robots, apply control policies learned in simulation to the real robots.

Olga Russakovsky, Room 408

• Research Areas: computer vision, machine learning, deep learning, crowdsourcing, fairness&bias in AI
• Design a semantic segmentation deep learning model that can operate in a zero-shot setting (i.e., recognize and segment objects not seen during training)
• Develop a deep learning classifier that is impervious to protected attributes (such as gender or race) that may be erroneously correlated with target classes
• Build a computer vision system for the novel task of inferring what object (or part of an object) a human is referring to when pointing to a single pixel in the image. This includes both collecting an appropriate dataset using crowdsourcing on Amazon Mechanical Turk, creating a new deep learning formulation for this task, and running extensive analysis of both the data and the model

Sebastian Seung, Princeton Neuroscience Institute, Room 153

• Research Areas: computational neuroscience, connectomics, "deep learning" neural networks, social computing, crowdsourcing, citizen science
• Gamification of neuroscience (EyeWire  2.0)
• Semantic segmentation and object detection in brain images from microscopy
• Computational analysis of brain structure and function
• Neural network theories of brain function

Jaswinder Pal Singh, Room 324

• Research Areas: Boundary of technology and business/applications; building and scaling technology companies with special focus at that boundary; parallel computing systems and applications: parallel and distributed applications and their implications for software and architectural design; system software and programming environments for multiprocessors.
• Develop a startup company idea, and build a plan/prototype for it.
• Explore tradeoffs at the boundary of technology/product and business/applications in a chosen area.
• Study and develop methods to infer insights from data in different application areas, from science to search to finance to others. 
• Design and implement a parallel application. Possible areas include graphics, compression, biology, among many others. Analyze performance bottlenecks using existing tools, and compare programming models/languages.
• Design and implement a scalable distributed algorithm.

Mona Singh, Room 420

• Research Areas: computational molecular biology, as well as its interface with machine learning and algorithms.
• Whole and cross-genome methods for predicting protein function and protein-protein interactions.
• Analysis and prediction of biological networks.
• Computational methods for inferring specific aspects of protein structure from protein sequence data.
• Any other interesting project in computational molecular biology.

Robert Tarjan, 194 Nassau St., Room 308

Available for single-semester IW and senior thesis advising, 2022-2023

• Research Areas: Data structures; graph algorithms; combinatorial optimization; computational complexity; computational geometry; parallel algorithms.
• Implement one or more data structures or combinatorial algorithms to provide insight into their empirical behavior.
• Design and/or analyze various data structures and combinatorial algorithms.

Olga Troyanskaya, Room 320

• Research Areas: Bioinformatics; analysis of large-scale biological data sets (genomics, gene expression, proteomics, biological networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bioinformatics.
• Implement and evaluate one or more gene expression analysis algorithm.
• Develop algorithms for assessment of performance of genomic analysis methods.
• Develop, implement, and evaluate visualization tools for heterogeneous biological data.

David Walker, Room 211

• Research Areas: Programming languages, type systems, compilers, domain-specific languages, software-defined networking and security
• Independent Research Topics:  Any other interesting project that involves humanitarian hacking, functional programming, domain-specific programming languages, type systems, compilers, software-defined networking, fault tolerance, language-based security, theorem proving, logic or logical frameworks.

Shengyi Wang, Postdoctoral Research Associate, Room 216

• Independent Research topics: Explore Escher-style tilings using (introductory) group theory and automata theory to produce beautiful pictures.

Kevin Wayne, Corwin Hall, Room 040

• Research Areas: design, analysis, and implementation of algorithms; data structures; combinatorial optimization; graphs and networks.
• Design and implement computer visualizations of algorithms or data structures.
• Develop pedagogical tools or programming assignments for the computer science curriculum at Princeton and beyond.
• Develop assessment infrastructure and assessments for MOOCs.

Matt Weinberg, 194 Nassau St., Room 222

• Research Areas: algorithms, algorithmic game theory, mechanism design, game theoretical problems in {Bitcoin, networking, healthcare}.
• Theoretical questions related to COS 445 topics such as matching theory, voting theory, auction design, etc. 
• Theoretical questions related to incentives in applications like Bitcoin, the Internet, health care, etc. In a little bit more detail: protocols for these systems are often designed assuming that users will follow them. But often, users will actually be strictly happier to deviate from the intended protocol. How should we reason about user behavior in these protocols? How should we design protocols in these settings?

Huacheng Yu, Room 310

• data structures
• streaming algorithms
• design and analyze data structures / streaming algorithms
• prove impossibility results (lower bounds)
• implement and evaluate data structures / streaming algorithms

Ellen Zhong, Room 314

No longer available for single-term IW  and senior thesis advising, 2023-2024

Opportunities outside the department

We encourage students to look in to doing interdisciplinary computer science research and to work with professors in departments other than computer science.  However, every CS independent work project must have a strong computer science element (even if it has other scientific or artistic elements as well.)  To do a project with an adviser outside of computer science you must have permission of the department.  This can be accomplished by having a second co-adviser within the computer science department or by contacting the independent work supervisor about the project and having he or she sign the independent work proposal form.

Here is a list of professors outside the computer science department who are eager to work with computer science undergraduates.

Maria Apostolaki, Engineering Quadrangle, C330

• Research areas: Computing & Networking, Data & Information Science, Security & Privacy

Branko Glisic, Engineering Quadrangle, Room E330

• Documentation of historic structures
• Cyber physical systems for structural health monitoring
• Developing virtual and augmented reality applications for documenting structures
• Applying machine learning techniques to generate 3D models from 2D plans of buildings
•  Contact : Rebecca Napolitano, rkn2 (@princeton.edu)

Mihir Kshirsagar, Sherrerd Hall, Room 315

Center for Information Technology Policy.

• Consumer protection
• Content regulation
• Competition law
• Economic development
• Surveillance and discrimination

Sharad Malik, Engineering Quadrangle, Room B224

Select a Senior Thesis Adviser for the 2020-21 Academic Year.

• Design of reliable hardware systems
• Verifying complex software and hardware systems

Prateek Mittal, Engineering Quadrangle, Room B236

• Internet security and privacy 
• Social Networks
• Privacy technologies, anonymous communication
• Network Science
• Internet security and privacy: The insecurity of Internet protocols and services threatens the safety of our critical network infrastructure and billions of end users. How can we defend end users as well as our critical network infrastructure from attacks?
• Trustworthy social systems: Online social networks (OSNs) such as Facebook, Google+, and Twitter have revolutionized the way our society communicates. How can we leverage social connections between users to design the next generation of communication systems?
• Privacy Technologies: Privacy on the Internet is eroding rapidly, with businesses and governments mining sensitive user information. How can we protect the privacy of our online communications? The Tor project (https://www.torproject.org/) is a potential application of interest.

Ken Norman,  Psychology Dept, PNI 137

• Research Areas: Memory, the brain and computation 
• Lab:  Princeton Computational Memory Lab

Potential research topics

• Methods for decoding cognitive state information from neuroimaging data (fMRI and EEG) 
• Neural network simulations of learning and memory

Caroline Savage

Office of Sustainability, Phone:(609)258-7513, Email: cs35 (@princeton.edu)

The  Campus as Lab  program supports students using the Princeton campus as a living laboratory to solve sustainability challenges. The Office of Sustainability has created a list of campus as lab research questions, filterable by discipline and topic, on its  website .

An example from Computer Science could include using  TigerEnergy , a platform which provides real-time data on campus energy generation and consumption, to study one of the many energy systems or buildings on campus. Three CS students used TigerEnergy to create a  live energy heatmap of campus .

Other potential projects include:

• Apply game theory to sustainability challenges
• Develop a tool to help visualize interactions between complex campus systems, e.g. energy and water use, transportation and storm water runoff, purchasing and waste, etc.
• How can we learn (in aggregate) about individuals’ waste, energy, transportation, and other behaviors without impinging on privacy?

Janet Vertesi, Sociology Dept, Wallace Hall, Room 122

• Research areas: Sociology of technology; Human-computer interaction; Ubiquitous computing.
• Possible projects: At the intersection of computer science and social science, my students have built mixed reality games, produced artistic and interactive installations, and studied mixed human-robot teams, among other projects.

David Wentzlaff, Engineering Quadrangle, Room 228

Computing, Operating Systems, Sustainable Computing.

• Instrument Princeton's Green (HPCRC) data center
• Investigate power utilization on an processor core implemented in an FPGA
• Dismantle and document all of the components in modern electronics. Invent new ways to build computers that can be recycled easier.
• Other topics in parallel computer architecture or operating systems

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101 Best Computer Science Topics for 2023

Any student will know the difficulty that comes with developing and choosing a great topic in computer science. Generally speaking, a good topic should be original, interesting, and challenging. It should push the limits of the field of study while still adequately answering the main questions brought on by the study.

We understand the stress that this may cause students, which is why we’ve dedicated our time to search the web and print resources to find the latest computer science topics that create the biggest waves in the field. Here’s the list of the top computer science research topics for 2023 you can use for an essay or senior thesis :

AP Computer Science Topics for Students Entering College

• How has big data impacted the way small businesses conduct market research?
• Does machine learning negatively impact the way neurons in the brain work?
• Did biotech change how medicine is administered to patients?
• How is human perception affected by virtual reality technologies?
• How can education benefit from using virtual reality in learning?
• Are quantum computers the way of the future or are they just a fad?
• Has the Covid-19 pandemic delayed advancements in computer science?

Computer Science Research Paper Topics for High School

• How successful has distance learning computer tech been in the time of Covid-19?
• Will computer assistance in businesses get rid of customer service needs?
• How has encryption and decryption technology changed in the last 20 years?
• Can AI impact computer management and make it automated?
• Why do programmers avoid making a universal programming language?
• How important are human interactions with computer development?
• How will computers change in the next five to ten years?

Controversial Topics in Computer Science for Grad Students

• What is the difference between math modeling and art?
• How are big-budget Hollywood films being affected by CGI technologies?
• Should students be allowed to use technology in classrooms other than comp science?
• How important is it to limit the amount of time we spend using social media?
• Are quantum computers for personal or home use realistic?
• How are embedded systems changing the business world?
• In what ways can human-computer interactions be improved?

Computer Science Capstone Project Ideas for College Courses

• What are the physical limitations of communication and computation?
• Is SCRUM methodology still viable for software development?
• Are ATMs still secure machines to access money or are they a threat?
• What are the best reasons for using open source software?
• The future of distributed systems and its use in networks?
• Has the increased use of social media positively or negatively affected our relationships?
• How is machine learning impacted by artificial intelligence?

Interesting Computer Science Topics for College Students

• How has Blockchain impacted large businesses?
• Should people utilize internal chips to track their pets?
• How much attention should we pay to the content we read on the web?
• How can computers help with human genes sequencing?
• What can be done to enhance IT security in financial institutions?
• What does the digitization of medical fields mean for patients’ privacy?
• How efficient are data back-up methods in business?

Hot Topics in Computer Science for High School Students

• Is distance learning the new norm for earning postgraduate degrees?
• In reaction to the Covid-19 pandemic should more students take online classes?
• How can game theory aid in the analysis of algorithms?
• How can technology impact future government elections?
• Why are there fewer females in the computer science field?
• Should the world’s biggest operating systems share information?
• Is it safe to make financial transactions online?

Ph.D. Research Topics in Computer Science for Grad Students

• How can computer technology help professional athletes improve performance?
• How have Next Gen Stats changed the way coaches game plan?
• How has computer technology impacted medical technology?
• What impact has MatLab software had in the medical engineering field?
• How does self-adaptable application impact online learning?
• What does the future hold for information technology?
• Should we be worried about addiction to computer technology?

Computer Science Research Topics for Undergraduates

• How has online sports gambling changed IT needs in households?
• In what ways have computers changed learning environments?
• How has learning improved with interactive multimedia and similar technologies?
• What are the psychological perspectives on IT advancements?
• What is the balance between high engagement and addiction to video games?
• How has the video gaming industry changed over the decades?
• Has social media helped or damaged our communication habits?

Research Paper Topics in Computer Science

• What is the most important methodology in project planning?
• How has technology improved people’s chances of winning in sports betting?
• How has artificial technology impacted the U.S. economy?
• What are the most effective project management processes in IT?
• How can IT security systems help the practice of fraud score generation?
• Has technology had an impact on religion?
• How important is it to keep your social networking profiles up to date?

More Computer Science Research Papers Topics

• There is no area of human society that is not impacted by AI?
• How adaptive learning helps today’s professional world?
• Does a computer program code from a decade ago still work?
• How has medical image analysis changed because of IT?
• What are the ethical concerns that come with data mining?
• Should colleges and universities have the right to block certain websites?
• What are the major components of math computing?

Computer Science Thesis Topics for College Students

• How can logic and sets be used in computing?
• How has online gambling impacted in-person gambling?
• How did the 5-G network generation change communication?
• What are the biggest challenges to IT due to Covid-19?
• Do you agree that assembly language is a new way to determine data-mine health?
• How can computer technology help track down criminals?
• Is facial recognition software a violation of privacy rights?

Quick and Easy Computer Science Project Topics

• Why do boys and girls learn the technology so differently?
• How effective are computer training classes that target young girls?
• How does technology affect how medicines are administered?
• Will further advancements in technology put people out of work?
• How has computer science changed the way teachers educate?
• Which are the most effective ways of fighting identify theft?

Excellent Computer Science Thesis Topic Ideas

• What are the foreseeable business needs computers will fix?
• What are the pros and cons of having smart home technology?
• How does computer modernization at the office affect productivity?
• How has computer technology led to more job outsourcing?
• Do self-service customer centers sufficiently provide solutions?
• How can a small business compete without updated computer products?

Computer Science Presentation Topics

• What does the future hold for virtual reality?
• What are the latest innovations in computer science?
• What are the pros and cons of automating everyday life?
• Are hackers a real threat to our privacy or just to businesses?
• What are the five most effective ways of storing personal data?
• What are the most important fundamentals of software engineering?

Even More Topics in Computer Science

• In what ways do computers function differently from human brains?
• Can world problems be solved through advancements in video game technology?
• How has computing helped with the mapping of the human genome?
• What are the pros and cons of developing self-operating vehicles?
• How has computer science helped developed genetically modified foods?
• How are computers used in the field of reproductive technologies?

Our team of academic experts works around the clock to bring you the best project topics for computer science student. We search hundreds of online articles, check discussion boards, and read through a countless number of reports to ensure our computer science topics are up-to-date and represent the latest issues in the field. If you need assistance developing research topics in computer science or need help editing or writing your assignment, we are available to lend a hand all year. Just send us a message “ help me write my thesis ” and we’ll put you in contact with an academic writer in the field.

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Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic. 

Overview: CompSci Research Topics

• Algorithms & data structures
• Artificial intelligence ( AI )
• Computer networking
• Database systems
• Human-computer interaction
• Information security (IS)
• Software engineering
• Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

• An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
• A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
• An evaluation of machine learning algorithms used for recommender systems in streaming services
• A review of approximation algorithm approaches for solving NP-hard problems
• An analysis of parallel algorithms for high-performance computing of genomic data
• The influence of data structures on optimal algorithm design and performance in Fintech
• A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
• A comparison of streaming algorithm performance for the detection of elephant flows
• A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
• Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
• Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
• A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
• A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
• Exploring the feasibility of applying information theory to feature extraction in retail datasets.
• Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

• Applying deep learning algorithms for speech recognition in speech-impaired children
• A review of the impact of artificial intelligence on decision-making processes in stock valuation
• An evaluation of reinforcement learning algorithms used in the production of video games
• An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
• An analysis of the ethical and social implications of artificial intelligence-based automated marking
• The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
• An examination of the use of artificial intelligence in orthopaedic surgery
• The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
• An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
• A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Topics & Ideas: Networking

• An analysis of the impact of 5G technology on internet penetration in rural Tanzania
• Assessing the role of software-defined networking (SDN) in modern cloud-based computing
• A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
• Exploring the influence of cloud computing on security risks in fintech.
• An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
• Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
• An evaluation of the challenges and opportunities in 6G wireless network adoption
• The role of network congestion control algorithms in improving network performance on streaming platforms
• An analysis of network coding-based approaches for data security
• Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Topics & Ideas: Database Systems

• An analysis of big data management systems and technologies used in B2B marketing
• The impact of NoSQL databases on data management and analysis in smart cities
• An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
• Exploring the role of data warehousing and business intelligence in global consultancies
• An analysis of the use of graph databases for data modelling and analysis in recommendation systems
• The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
• An examination of the challenges and opportunities of distributed databases in supply chain management
• Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
• An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
• Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

• An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
• An exploration of how artificial intelligence is changing human-computer interaction patterns in children
• An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
• Assessing the influence of virtual and augmented reality on consumer purchasing patterns
• An examination of the use of gesture-based interfaces in architecture
• Exploring the impact of ease of use in wearable technology on geriatric user
• Evaluating the ramifications of gamification in the Metaverse
• A systematic review of user experience (UX) design advances associated with Augmented Reality
• A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
• Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

Topics & Ideas: Information Security

• A bibliometric review of current trends in cryptography for secure communication
• An analysis of secure multi-party computation protocols and their applications in cloud-based computing
• An investigation of the security of blockchain technology in patient health record tracking
• A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
• A systematic review of secure data storage solutions used for cloud computing in the fintech industry
• An analysis of intrusion detection and prevention systems used in the healthcare sector
• Assessing security best practices for IoT devices in political offices
• An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
• A comparative study of digital signature schemes adoption in property transfers
• An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

• A study of agile software development methodologies and their impact on project success in pharmacology
• Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
• A study of the impact of DevOps practices on software development and delivery in the healthcare sector
• An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
• A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
• An investigation of software testing techniques and methodologies for subscription-based offerings
• A review of software security practices and techniques for protecting against phishing attacks from social media
• An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
• Exploring the impact of software development outsourcing on project success in multinational contexts
• An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

• An array-based optimization framework for query processing and data analytics (Chen, 2021)
• Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
• Embedding constructural documentation in unit tests (Nassif, 2019)
• PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
• Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
• Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
• Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
• Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
• Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
• Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
• Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
• A state-based approach to context modeling and computing (Yue, 2019)
• A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
• HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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Investigating the impacts of software refactoring techniques and tools in blockchain-based developments.

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The Future of AI Research: 20 Thesis Ideas for Undergraduate Students in Machine Learning and Deep Learning for 2023!

A comprehensive guide for crafting an original and innovative thesis in the field of ai..

By Aarafat Islam

“The beauty of machine learning is that it can be applied to any problem you want to solve, as long as you can provide the computer with enough examples.” — Andrew Ng

This article provides a list of 20 potential thesis ideas for an undergraduate program in machine learning and deep learning in 2023. Each thesis idea includes an  introduction , which presents a brief overview of the topic and the  research objectives . The ideas provided are related to different areas of machine learning and deep learning, such as computer vision, natural language processing, robotics, finance, drug discovery, and more. The article also includes explanations, examples, and conclusions for each thesis idea, which can help guide the research and provide a clear understanding of the potential contributions and outcomes of the proposed research. The article also emphasized the importance of originality and the need for proper citation in order to avoid plagiarism.

1. Investigating the use of Generative Adversarial Networks (GANs) in medical imaging:  A deep learning approach to improve the accuracy of medical diagnoses.

Introduction:  Medical imaging is an important tool in the diagnosis and treatment of various medical conditions. However, accurately interpreting medical images can be challenging, especially for less experienced doctors. This thesis aims to explore the use of GANs in medical imaging, in order to improve the accuracy of medical diagnoses.

2. Exploring the use of deep learning in natural language generation (NLG): An analysis of the current state-of-the-art and future potential.

Introduction:  Natural language generation is an important field in natural language processing (NLP) that deals with creating human-like text automatically. Deep learning has shown promising results in NLP tasks such as machine translation, sentiment analysis, and question-answering. This thesis aims to explore the use of deep learning in NLG and analyze the current state-of-the-art models, as well as potential future developments.

3. Development and evaluation of deep reinforcement learning (RL) for robotic navigation and control.

Introduction:  Robotic navigation and control are challenging tasks, which require a high degree of intelligence and adaptability. Deep RL has shown promising results in various robotics tasks, such as robotic arm control, autonomous navigation, and manipulation. This thesis aims to develop and evaluate a deep RL-based approach for robotic navigation and control and evaluate its performance in various environments and tasks.

4. Investigating the use of deep learning for drug discovery and development.

Introduction:  Drug discovery and development is a time-consuming and expensive process, which often involves high failure rates. Deep learning has been used to improve various tasks in bioinformatics and biotechnology, such as protein structure prediction and gene expression analysis. This thesis aims to investigate the use of deep learning for drug discovery and development and examine its potential to improve the efficiency and accuracy of the drug development process.

5. Comparison of deep learning and traditional machine learning methods for anomaly detection in time series data.

Introduction:  Anomaly detection in time series data is a challenging task, which is important in various fields such as finance, healthcare, and manufacturing. Deep learning methods have been used to improve anomaly detection in time series data, while traditional machine learning methods have been widely used as well. This thesis aims to compare deep learning and traditional machine learning methods for anomaly detection in time series data and examine their respective strengths and weaknesses.

Photo by  Joanna Kosinska  on  Unsplash

6. Use of deep transfer learning in speech recognition and synthesis.

Introduction:  Speech recognition and synthesis are areas of natural language processing that focus on converting spoken language to text and vice versa. Transfer learning has been widely used in deep learning-based speech recognition and synthesis systems to improve their performance by reusing the features learned from other tasks. This thesis aims to investigate the use of transfer learning in speech recognition and synthesis and how it improves the performance of the system in comparison to traditional methods.

7. The use of deep learning for financial prediction.

Introduction:  Financial prediction is a challenging task that requires a high degree of intelligence and adaptability, especially in the field of stock market prediction. Deep learning has shown promising results in various financial prediction tasks, such as stock price prediction and credit risk analysis. This thesis aims to investigate the use of deep learning for financial prediction and examine its potential to improve the accuracy of financial forecasting.

8. Investigating the use of deep learning for computer vision in agriculture.

Introduction:  Computer vision has the potential to revolutionize the field of agriculture by improving crop monitoring, precision farming, and yield prediction. Deep learning has been used to improve various computer vision tasks, such as object detection, semantic segmentation, and image classification. This thesis aims to investigate the use of deep learning for computer vision in agriculture and examine its potential to improve the efficiency and accuracy of crop monitoring and precision farming.

9. Development and evaluation of deep learning models for generative design in engineering and architecture.

Introduction:  Generative design is a powerful tool in engineering and architecture that can help optimize designs and reduce human error. Deep learning has been used to improve various generative design tasks, such as design optimization and form generation. This thesis aims to develop and evaluate deep learning models for generative design in engineering and architecture and examine their potential to improve the efficiency and accuracy of the design process.

10. Investigating the use of deep learning for natural language understanding.

Introduction:  Natural language understanding is a complex task of natural language processing that involves extracting meaning from text. Deep learning has been used to improve various NLP tasks, such as machine translation, sentiment analysis, and question-answering. This thesis aims to investigate the use of deep learning for natural language understanding and examine its potential to improve the efficiency and accuracy of natural language understanding systems.

Photo by  UX Indonesia  on  Unsplash

11. Comparing deep learning and traditional machine learning methods for image compression.

Introduction:  Image compression is an important task in image processing and computer vision. It enables faster data transmission and storage of image files. Deep learning methods have been used to improve image compression, while traditional machine learning methods have been widely used as well. This thesis aims to compare deep learning and traditional machine learning methods for image compression and examine their respective strengths and weaknesses.

12. Using deep learning for sentiment analysis in social media.

Introduction:  Sentiment analysis in social media is an important task that can help businesses and organizations understand their customers’ opinions and feedback. Deep learning has been used to improve sentiment analysis in social media, by training models on large datasets of social media text. This thesis aims to use deep learning for sentiment analysis in social media, and evaluate its performance against traditional machine learning methods.

13. Investigating the use of deep learning for image generation.

Introduction:  Image generation is a task in computer vision that involves creating new images from scratch or modifying existing images. Deep learning has been used to improve various image generation tasks, such as super-resolution, style transfer, and face generation. This thesis aims to investigate the use of deep learning for image generation and examine its potential to improve the quality and diversity of generated images.

14. Development and evaluation of deep learning models for anomaly detection in cybersecurity.

Introduction:  Anomaly detection in cybersecurity is an important task that can help detect and prevent cyber-attacks. Deep learning has been used to improve various anomaly detection tasks, such as intrusion detection and malware detection. This thesis aims to develop and evaluate deep learning models for anomaly detection in cybersecurity and examine their potential to improve the efficiency and accuracy of cybersecurity systems.

15. Investigating the use of deep learning for natural language summarization.

Introduction:  Natural language summarization is an important task in natural language processing that involves creating a condensed version of a text that preserves its main meaning. Deep learning has been used to improve various natural language summarization tasks, such as document summarization and headline generation. This thesis aims to investigate the use of deep learning for natural language summarization and examine its potential to improve the efficiency and accuracy of natural language summarization systems.

Photo by  Windows  on  Unsplash

16. Development and evaluation of deep learning models for facial expression recognition.

Introduction:  Facial expression recognition is an important task in computer vision and has many practical applications, such as human-computer interaction, emotion recognition, and psychological studies. Deep learning has been used to improve facial expression recognition, by training models on large datasets of images. This thesis aims to develop and evaluate deep learning models for facial expression recognition and examine their performance against traditional machine learning methods.

17. Investigating the use of deep learning for generative models in music and audio.

Introduction:  Music and audio synthesis is an important task in audio processing, which has many practical applications, such as music generation and speech synthesis. Deep learning has been used to improve generative models for music and audio, by training models on large datasets of audio data. This thesis aims to investigate the use of deep learning for generative models in music and audio and examine its potential to improve the quality and diversity of generated audio.

18. Study the comparison of deep learning models with traditional algorithms for anomaly detection in network traffic.

Introduction:  Anomaly detection in network traffic is an important task that can help detect and prevent cyber-attacks. Deep learning models have been used for this task, and traditional methods such as clustering and rule-based systems are widely used as well. This thesis aims to compare deep learning models with traditional algorithms for anomaly detection in network traffic and analyze the trade-offs between the models in terms of accuracy and scalability.

19. Investigating the use of deep learning for improving recommender systems.

Introduction:  Recommender systems are widely used in many applications such as online shopping, music streaming, and movie streaming. Deep learning has been used to improve the performance of recommender systems, by training models on large datasets of user-item interactions. This thesis aims to investigate the use of deep learning for improving recommender systems and compare its performance with traditional content-based and collaborative filtering approaches.

20. Development and evaluation of deep learning models for multi-modal data analysis.

Introduction:  Multi-modal data analysis is the task of analyzing and understanding data from multiple sources such as text, images, and audio. Deep learning has been used to improve multi-modal data analysis, by training models on large datasets of multi-modal data. This thesis aims to develop and evaluate deep learning models for multi-modal data analysis and analyze their potential to improve performance in comparison to single-modal models.

I hope that this article has provided you with a useful guide for your thesis research in machine learning and deep learning. Remember to conduct a thorough literature review and to include proper citations in your work, as well as to be original in your research to avoid plagiarism. I wish you all the best of luck with your thesis and your research endeavors!

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Thesis Helpers

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105 Computer Science Thesis Topics And Writing Guide

After years of hard work and struggle, you have reached the most important stage of your academic life – writing a computer science thesis. It is clear that this is a defining moment for your life, and you wouldn’t want to throw anything to chance.

As a rule, most of the computer science theses consist of two major parts – writing a particular program and writing a paper, describing its functionality and the reasons behind its development.

Whether yours is a computer science bachelor thesis, computer science Master’s thesis, or a computer science Ph.D. thesis, you know it is not easy. With all the algorithms, binary equations, and programming calculations in your head, you might end up breaking down.

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Computer Science Thesis Outline: How To Structure It?

Like any other academic research paper, a computer science thesis has a well-laid out structure that you will follow. An outline helps underpin the bulk of such a demanding paper into manageable parts.

Before we delve into this, we have to understand that there are various computer science fields such as:

Computer hardware systems Software systems Database systems Discrete mathematics Scientific computing

Therefore, whenever you determine the outline of your bachelor’s or master thesis computer science outline, bear those categories in mind. They will help you narrow down your research to a specific area, thus saving you time and energy too!

Depending on your institution, you will have a specified outline for your computer science thesis. However, the following parts form the standard outline of any thesis paper for Masters or Ph.D.

• Introduction (contains the background, statement of the problem, research questions, hypothesis, etc.)
• Next is the literature review , which gives the theoretical framework of your research
• The methodology section describes and justifies the methods to be used in data collection.
• The results and discussion section gives answers to your research questions and explains their meaning.
• Finally, the conclusion and recommendations review the findings and results and give a summary of the research.

The outline of a Master’s thesis in Computer Science or Ph. D. might vary depending on its requirements. Be sure to confirm with your professor on which outline to follow.

Master Thesis Computer Science Writing Guide

Writing such a large scale project is not something that can be done in a few days. The technicality of the computer science field makes it all the more complex. Some will tell you that it is more technical than coming up with a computer program.

That said, here are professionally handpicked tips for your Master Thesis in Computer Science:

• Understand the purpose of your computer thesis If you are writing on a computer program, show a deeper knowledge and understanding of the unique and fresh program. Let the reader see that you have mastered your program to the core.
• Begin writing early It is not something you can plan to do on the eve of the submission date. It will make your writing process light and highly motivational, especially with the voluminous books you will have to read.
• Selecting your topic It is a task that sends chills down the spine of many students. Thus, your topic should not be too narrow or too broad – this will portray you as an amateur. Draw your computer science thesis topic from something you encountered during your coursework.
• Keep reading To be precise, read a little, write a little, every day. It will surprise you how much ground you will have covered by the time you are submitting your thesis for review.

Latest Computer Science Thesis Topics For You!

Below is a comprehensive list of original computer science thesis topics for your inspiration:

• A case study of the pitfalls of assembly languages used to develop applications, websites, and software.
• Design and development of artificial intelligence systems
• Process improvement techniques for the functionality of robots
• An analysis of the factors that necessitate Java as one of the best programming languages
• What is the place of ethical hacking in today’s digital society?
• How to improve human-computer interaction
• What is the potential of computer systems in combating terrorism and crime?
• Identify how cyber-security enhances data confidentiality
• The design and engineering of computer applications and other systems
• Highlighting the differences between programming languages
• How can organizations make use of data mining?
• Identify efficient logistics in software architecture
• The effect of globalization and its impact on database administration
• A detailed investigation into the data availability and security
• The influence and impact of emerging computer technologies on the healthcare system
• Effect of training on knowledge performance in computer performance optimization
• The behavior of network architecture within a computing environment
• How can learning institutions implement computer systems for virtual and distance learning?
• Why risk management is necessary for data protection and information security in companies
• A detailed review of the role of education and industrialization on the development of computer systems.

From these topics, you can derive more computer science thesis topics for your presentation. Remember that the topic should be on a subject or field that is of interest to you. Settling on a complex and least researched topic might not be a good idea for you.

We can help you unearth more topics for your thesis paper. Read to the end to find out how?

Computer Science Thesis Topics

You need a computer science thesis topic before getting a computer science degree. Here is a list of interesting topics to create the best essay yet:

• Explain how to Blockchain benefits big businesses
• Discuss the conversation on using pet tracking chips
• Examine how genetic sequencing works using a computer
• How does IT help with security in financial institutions?
• Discuss what digitization means for privacy in the medical field
• What are the most effective ways to backup data in the medical field?
• Discuss the limitations of communication and computation
• Would you say the average ATM is secure?
• Analyze an innovation that seems threatening but seems to be a favorite for the human race
• Why should any business utilize open-source software, and how does it help with security?
• Discuss the role of technology in the classroom
• Discuss the personal or home use of quantum computers
• Would you say embedded systems are changing how the world works?
• What would you say about social media and technology trends
• Will technology reduce recruitment in an industry (of your choosing)
• How does technology affect human interactions, and will AI remedy that?
• Examine the computer assistance that can help businesses perform efficient customer care
• Analyze the technologies involved in casino live gambling
• Would you say artificial intelligence is a threat or blessing to contemporary society
• Explain if machine learning impact neurons and the way the brain works negatively
• How does Big Data help corporations
• Examine the average human’s knowledge of virtual reality through quantitative research
• Philosophize the future of technology
• Examine the future of programming languages and their efficiency
• What is the most creative development in computer technology yet?

Computer Science Topics

If you are fascinated by computer science and technology, you may want to conduct in-depth research into several fields. Here are interesting topics for a computer science thesis to review:

• Discuss databases, data mining, and how cryptocurrency works
• Examine the network between neuron network and machine learning
• How do robots and computers understand human language
• Examine the role of mathematics in modeling computers
• Discuss encryption and decryption of data
• How does computer-aided learning work
• How can you achieve usability in human-computer interaction
• Are there any hacking ethics?
• Discuss the advantages and disadvantages of the cloud storage
• What are the cybersecurity threats in banking systems
• Are there any loopholes in the technology of DAOs
• How does Blockchain Technology help the world
• Discuss the role of wireless systems in vehicles
• Examine how biometric systems work in cars
• Analyze how cryptography works.

Computer Science Research Topics

If you’ve ever wondered how technology and the world cooperate, here are some of the best topics to research and provide answers to for your essay or paper.

• What is the nexus of technology and finance?
• Examine the relationship between technology and healthcare
• Can robots work without any human intervention?
• How do computers interfere with forensics?
• Discuss computer security and information and how they work
• Examine the concerns of privacy in electronic health
• What are the vulnerabilities in bioinformatics?
• Explain the buildup of cyber-physical systems
• How has deep learning helped an industry of your choice
• What are the process computer take to analyze language
• Discuss the basic techniques for computer security
• Examine how natural language processing works
• Give an overview of textual mining
• How do deep visual models work?
• What is meant by distributed data clustering?

Research Topics in Computer Science

Computer science deals with how computer systems work. It is all about computer programs, strategies for development, and how they help humans. Here are 15 topics for you:

• Examine the role of computer technology in sports
• How does technology boost the performance of professional athletes?
• Would you say technology can lead to addiction?
• Explore the strategies used in gaming technology
• How does computer technology influence management solutions?
• Discuss the role of technology in the engineering field
• What is the future of information technology?
• What are the key developments and trends that show the vulnerabilities of technology?
• Using Tesla as a case study, what are technology’s vulnerabilities in automobile manufacturing and development.
• What does psychology say about the different Advancements in technology
• Examine the evolution of the gaming industry and how it has changed the perception of entertainment
• Track the evolution of the entertainment industry and technology has helped propel it
• What are the ways technology has propelled interactive media?
• Discuss the ways technology has influenced sports betting
• How has technology helped with fraud detection in the finance sector?

Computer Science Topics for Research

Being a computer science student means brainstorming, researching, and giving in-depth interpretations of why and how some things happen. Here are some relevant computer science research topics to steer your critical thinking skills:

• Analyze technological innovations in the construction and real estate industries
• Can AI have an impact on the economy of any country?
• Technology has helped with the way we understand the environment: argue
• Can technology help with how we solve the climate crisis?
• What is the role of technology in social media marketing?
• Discuss the technology companies like Google use to offer internet services
• Deeply analyze why some Mobile phones cannot work in the US
• How does the technology work in the creation of smart home systems?
• Data mining and ethical concerns: what are they?
• Will the 5-G network change how phones connect?
• Discuss the most important technology trends since COVID-19
• Why is facial scanning vulnerable to privacy breaches?
• How can computer technology help in tracking crime and offenders?
• What is the core buildup of math computing?
• Explain the most effective and ethical ways to tackle identity theft.

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IT & Computer Science THESIS AND RESEARCH TOPICS

Information technology (IT) and computer science research topics propel the digital age and landscape, shaping AI, cybersecurity, and user-friendly interfaces to revolutionize industries, societies, and human experiences. View all our IT and computer science thesis topics below.

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Overview of IT & Computer Science topics for bachelor and master thesis project

Find IT and computer science research topics and themes in artificial intelligence (AI), machine learning (ML), IT security, software engineering, data science, UX/UI, NLP, app development, human-computer interaction (HCI), and much more! Be inspired on your tech journey here.

• Technical University of Denmark
• Master of Science
• Spring 2024

IT & Computer Science

Web App Development

UI/UX Design

Knowledge Sharing

Validating and Testing

Knowledge Sharing Web Application Development Project

Interactive software development by engaging users and main stakeholders

Are you seeking a collaboration for developing a brand new or refine an already existing web based application? Then look no further, this is the right place to be as the main goal of this project is to provide the best possible results uniquely tailored to its stakeholders needs using a user-centric approach.  As a starting point, this is a Master's Thesis Project for which I am seeking collaborators and the first idea of the project is to develop a knowledge sharing platform with educatio...

1 x MSc in Engineering (Computer Science and Engineering)

• University of Southern Denmark

Design Innovation

Design research

Product innovation

User experiences on play

Research on experiences

Exploring the Lived Experience of Play: A Phenomenological Inquiry

How play is experienced and what the implications are for design.

The act of play is a fundamental aspect of human life, influencing various domains such as creativity, social interaction, well-being, and personal development. Despite its ubiquity, the subjective nature of play remains relatively unexplored. This research proposes a phenomenological inquiry into the lived experiences of play, aiming to uncover the intricate ways individuals engage with and perceive play in diverse contexts.   Background and Rationale:   Play encompasses a wide ra...

1 x Cand.it. i Produkt Design

• University of Copenhagen

Quantum Computing

Climate Modeling

Environmental Simulation

Algorithm Development

Data Analysis in Climate Science

Leveraging Quantum Computing for Enhanced Climate Modeling and Simulation

Harnessing Quantum Power for Climate Insights: A New Era in Environmental Modeling

Introduction With its ability to solve complex computational problems more efficiently than classical computing, quantum computing has emerged as a promising field. This thesis presents an opportunity to explore the application of quantum computing in the crucial domain of climate modeling and simulation. By developing and assessing quantum-enhanced models, we can achieve more accurate predictions of weather patterns, ocean currents, and the impact of greenhouse gases. This research has the pote...

1 x MSc in Computer Science

Digital Healthcare

Patient-Clinic Communication

Medical Data Security

Healthcare Mobile Application

Universal Patient-Clinic Communication Application

Overview  The proposed thesis focuses on developing a comprehensive application designed to streamline and enhance communication between patients and clinics. This multifunctional platform aims to cover all aspects of medical interaction, from appointment booking to surgery scheduling. It will facilitate the maintenance of digital medical records, including receipts and reports like scans and X-rays, ensuring transparency and accessibility for patients. Motivation: The primary motivation be...

Cybersecurity

Energy Consumption

IoT Architecture

Optimizing IoT Efficiency: Enhancing Performance While Ensuring Security

Advancing Energy-Efficient and Secure IoT Solutions: A Collaborative Research Initiative

In the era of digital transformation, the Internet of Things (IoT) stands as a cornerstone of innovation and efficiency. Our research project, titled "Optimizing IoT Efficiency: Enhancing Performance While Ensuring Security," aims to advance the standards of operational efficiency and security in IoT systems. Our thesis project will conduct an in-depth evaluation of your current IoT system architecture, focusing on optimizing energy usage while maintaining effective security. By dissecting the i...

1 x Cybersecurity

• Aalborg University

User Experience

Machine Learning

Digital Product Design

Data-driven Insights

User-Centered Design

Crafting Exceptional User Experiences: A Data-Driven Approach to Digital Product Design

Enhancing User Experience, Fostering Innovation, and Guiding Informed Decision-Making in Digital Product Development

Introduction  In today's dynamic digital landscape, organizations spanning diverse sectors face an ongoing challenge: the continuous enhancement of user experience (UX) and innovation in their digital products and services. This thesis proposal presents a dynamic framework that seamlessly merges user-centred design principles with data-driven insights, enhanced by machine learning, with a sharp focus on elevating UX and stimulating product innovation. This proposal outlines an adaptable fra...

1 x MSc in Information Science (Information Studies)

1 x Cand.it. i Information Science (Information Studies)

• Aarhus University

Cyber Security

Business Development

Cyber Security Strategies in an AI Generation

The unique challenges SME's face in securing their digital assets and data, and how they can implement robust security protocols in an AI generation.

This thesis will investigate practical, scalable cybersecurity strategies for small and medium-sized enterprises (SMEs). Recognizing the unique challenges SMEs face, such as limited budgets and expertise, the study will focus on identifying cybersecurity threats specific to SMEs and evaluating affordable, efficient security solutions with AI. The research will include a survey of current cybersecurity risks, an assessment of various security frameworks and tools suitable for SMEs, and interviews...

1 x Msc in Technology based Business Development

Optimization

Data Management

Education Sector

Optimization of Data Management and Compliance in the Education Sector through Chatbots

Enhancing Efficiency and Security with AI-Powered Solutions

I wish to examine how chatbots, powered by artificial intelligence (AI), can play a crucial role in optimizing data management and security compliance in the education sector. Chatbots have become increasingly sophisticated, and their potential in terms of data management and compliance is only beginning to be explored. The focus will be on key areas, such as the implementation of chatbots in the education sector, including how chatbots can be effectively integrated into the school's IT environm...

1 x Cand.it. i Webkommunikation

Rsk assesment

Quantative analysis

Data analysis

Machine Learning in the Financial Sector

Risk management, portfolio optimization

Machine Learning Project in Finance  The main goal for our Master Project is to implement different machine learning algorithms (including reinforcement learning and deep learning) in finance. We are mainly interested in testing the performance of these algorithms (with comparison to available approaches) in: 1.     Risk Assessment - assessing and managing risks in investment portfolios 2.     Portfolio Optimization - using algorithms to construct diversified portfolios ...

1 x MSc in Engineering (Business Analytics)

IT-implementation

Project management

Change management

Data mangement

Process innovation

IT-implementation in company X

Streamlining processes through IT/data

How can technology or data contribute to streamlining the daily work in a company? And how can the company, through effective management, motivate the company to use the technology or data correct? This is what I want to examine in my master thesis. The company or organisation can be in the public or private sector in any given industry. A potential research question can be as following: "How can the organisation X use technology Y to streamline workflow, and which implication can appear during ...

1 x Cand.it. i IT, Kommunikation og Organisation (ITKO)

Website Redesign

Usability Enhancement

User-Centric Redesign

Graphic Design

UI/UX Design with a prototype

This thesis in website redesign would focus on the comprehensive overhaul and optimization of an existing website. This project would involve a deep analysis of the current website's user experience, design, functionality, and performance. The aim is to identify shortcomings and areas for improvement, taking into account user feedback and industry best practices. The thesis would propose and implement innovative design concepts, user interface enhancements, and potentially, the integration of cu...

Software Engineering

Agile Methodology

User-Centric Software Engineering Project

Leveraging agile principles and domain knowledge to deliver valueable software product

Are you looking for an eager collaboration partner to aid in the design, implementation and/or testing of a high-value software system? Does the project frame and scope lend itself to a thesis collaboration? Then I would be honored to assist! Ideally I am seeking an opportunity to contribute to a new or existing software project that places a strong emphasis on agile methodologies, user-centric development, and the utilization of contemporary technologies. While collaboration within a team is de...

• Copenhagen Business School

Data Science

Deep Learning

Machine Learning applied to business context

How ML can bring value

The idea is to identify Machine Learning techniques that are appropriate to the existing framework of the company and industry. The main steps of Data Science Methodology will be applied:  -       Data Preprocessing with a focus on handling missing values, outliers, and noise.  -       Exploratory Data Analysis in order to uncover patterns, correlations, and potential anomalies within the data. -       Model Development: unsupervised/supervi...

1 x MSc in Business Administration and Data Science

• Master of Arts

communication

Thesis in Communication & IT

Open for suggestions

Hello! We are three cand.IT students from Communication & IT at Københavns Universitet looking for someone to collaborate with on our master thesis. We have experience with: Analysing datasets Developing ideas to optimise workflows Design and innovation in relation to interfaces and IT-systems Previously, we have collaborated with several companies in relation to our education. We are open for suggestions on specific issues in your organisation or company, on which you could use some in...

1 x Cand.mag. i Kommunikation og IT

Innovative Solutions

Data Science Students

Efficiency Improvements

CSR related activities

Financial background

Open to Fine-Tune Solutions in Partnership with Your Company

We are two dedicated MSc students in Business Analytics and Data Science, seeking an collaboration with a company for our thesis project. About Us: - We both have a strong academic background in finance and economics - Our shared interests revolve around utilizing big data analytics, algorithms, and machine learning models to optimize processes and enhance workflows. - We are passionate about sustainability and Corporate Social Responsibility (CSR) initiatives. - Together, we have successfully c...

Mental Health Assessment

Adaptive Personalized Care

Conversational AI

Digital Therapeutic Interaction

Development and Implementation of an AI-Driven Mental Health Tool for Adaptive Patient Assessment and Psychiatrist Matching

Conversational AI x Mental Health

In the realm of healthcare, technology-driven solutions have become essential to assist patients, therapists, and support networks. In the context of mental health, where personalized care is paramount, the development of thoughtfully crafted technological tools is imperative. Individuals facing mental health challenges require solutions that align with their unique needs and capabilities. A well-designed user interface (UI) and an enriching user experience (UX) are critical for ensuring that th...

1 x MSc in Engineering (Human-Centered Artificial Intelligence)

• Roskilde University
• Spring 2023

Data prediction using different machine learning models

Computer science

The main focus of this project is to work with real life problems and real life data. As the title suggests, we are thinking of using different methods to predict new data....

1 x Computer Science and Informatics

Research Interest

AI in practice

Internatiol Network

Human-ML Augmentation

How to improve fairness when augmenting human decisions with Machine Learning

MIS Quarterly The thesis will investigate how Machine Learning influences excisting Information Systems theories and their notions of fairness in collaboration and decision making. Artificial Intelligence and Machine Learning is already widely used and will be applied even more in the future. Sometimes machines are taught human biases and even extend those on a larger scale, this needs to be prevented by creating models sensitive to fairness. However in other cases machines and algorithms can en...

1 x Business Administration and Information Systems

• IT University of Copenhagen

Reduced costs

Process optimisation

Process automatisation from manual to automatic

Automatisation of a process

We are three student from IT-University who are writing a bachelor project focusing on processes. We are looking for a process were we can automate manual tasks with creating, storing or moving data in excel or other easy-accesible systems. The benefit of this automatizion will unlock possibilities for Business Intelligence and increased usage of the data and/or simply heap the benefits of reduced costs....

1 x Global Business Informatics

IT transformation

Participatory IT Design

Preliminary study in IT transformation

In recent years a lot of organizations are looking towards IT to solve business and organizational related problems. This means a lot of time and money are spend on a variety of projects, some with more success than others. This project is preliminary study of such a situation. Using the MUST-method, the project examines the feasibility of a future or existing IT solution to a given problem. The MUST-method is a hollistic approah where all affected parties in the organization is included, and ar...

1 x Software Development

Algorithmic management

human vs. technological

Efficiency and optimization

Bachelor thesis: Algorithmic Management in organizations

Bachelor of science - Global Business Informatics

We are a group of three Global Business Informatics students at ITU, in the midst of our bachelor's project. We share an interest in technologies that form and co-construct in relation to organizational structures and in that regard wish to explore this further with our project.  We intend to investigate the shifts in organizing principles that take form in the presence of algorithmic management technologies. We find this topic interesting due to the multiple aspects it presents: human vs. ...

Design process

User centered

Creative approach

Collaboration

How UX can help solve user pain points

Use our UX and design process skills to help illuminate problems and suggest solutions

We haven't set our minds on a thesis topic yet, but would rather use Excelerate as an opportunity for inspiration through collaboration. We are interested in finding user pain points or problematics, and through data collecting and design processes try to solve this problematics - potentially with Hi-Fi prototype(s). We hope to find these problematics through a collaboration, discussion or/and conversation with you as our potential partner. We especially find interest within the field of AI (fro...

1 x Digital Design and Interactive Technologies

• Spring 2022

Ethical application

Better algorithms

Ethical applicationen of AI

How to make ethical algorithms

A while back an algorithm was implemented in jobcentres that predicted who were at risk for becoming long-term unemployed. When implemented it predicted that people above the age of 60 and those whose parents came from other countries were more likely to become unemployed. The algorithm did not solve a problem with unemployment, but instead just predicted the biases that employers have when they are looking to hire new employees.Instead an algorithm that focused on competences might have been mo...

1 x IT Management

Universities

Plagiarism Detection Systems

Evaluating the Efficacy of University Plagiarism Detection Systems in Verifying Student Authenticity of Knowledge in the Era of ChatGPT

Ensuring Academic Integrity in the Age of ChatGPT: An Assessment of University Plagiarism Detection Systems and their Effectiveness in Verifying Student Knowledge Authenticity

This thesis aims to evaluate the efficacy of plagiarism detection systems used by universities in verifying the authenticity of students' knowledge, specifically in the context of ChatGPT and similar AI models. By assessing the capabilities and limitations of these systems within the university environment, this research will explore whether they can effectively identify instances of plagiarism involving AI-generated content and ensure the authenticity of student work.  ...

decision-making

data science

Creating a business reporting app, as a method of quick response to threats

Nowadays proper information is crucial to achieve success - how coding can help us with it

My idea is to write about giving a proper information about e.g. amount of sold products to the team and managersd. My field of study is Data Science, so I want to create an app which will automate process of informing management about organisation's results. My idea is to begin why it is crucial to inform a team frequently and indroducing main methods to do so (including review literature and comparing different methods of doing it). Later my idea is to move to methodology where I will create a...

1 x MSc in Social Data Science

Mobile App Development

Application

Navigation App

Android Studio

Alternative way to indicate directions for the user

Mobile App development

My idea is to create an app that would direct a user from place A to B by giving vibration signals to the user.  The app would have a map on the interface and the user would insert where they want to go. Then the map would give signals by vibrating when the user needs to turn left or right.  I argue this idea would be useful for people cycling if they don't want to have a phone in their hand while they cycle. Also if you run on a new route and you don't want to stop and check direction...

Digital Design

User Insights

Prototyping

UX Design in Digital Development

A case study focusing on user involvement in digital development to improve user experiences

We are looking for a partner to collaborate with for our thesis, to investigate a concrete case where we can use our methodologies from UX Design and digital design in general. We have a philosophy that is based on the assumption that user involvement enhances the user experiences. ...

Artificial Intelligence

The Importance of Machine Learning algorithms in the Health Sector

We are two master students currently studying Business Administration and Data Science at Copenhagen Business School. At the moment, we are starting our final year and we are therefore looking for a partner for our master's thesis. We want to specialize in the field of Machine Learning with a focus on the health sector, which is why we are making this account. ...

1 x Business Administration and Data Science

Modern organization

Cyber security risks in the modern organization (working title)

How to handle cyber security risks in a modern organization and the economic consequences hereof

"43% of cyber attacks are aimed at small businesses, but only 14% are prepared to defend themselves" [1] is a shocking but important statistic. As the cyber threat keeps growing, the modern organization needs to be prepared, as ignoring these threats can cause financial and reputational damage. It is simply something that cannot be ignored. Recent events, such as the Covid-19 outbreak has caused an organizational change in many companies around the world. "Home office" or remote work has become ...

Design Thinking

Real word case

How could we improve a company’s product by using a design thinking approach

Dive into each step of the design thinking project and compare it to their processes

How can we improve a company’s product/processes by using a design thinking approach  ...

1 x Problem Based Learning in Engineering and Science

Business strategy

Deploying MLOps in a live production setup - a demo case study to operationalize machine learning

Deploying MLOps – the most pivotal but also underrated component in machine learning: A demo case study on [insert use case theme here]

Our thesis aims to operationalise a machine learning workflow for a company or department that is interested to deploy a machine learning solution to enhance their work. The theoretical underpinnings of this machine learning workflow (also referred to as MLOps) will be based on materials stemming from different courses – ranging from infrastructural choices (e.g. Microsoft Azure, Databricks, AWS etc.), database choice (e.g. RDMBS vs NoSQL), database design theories, reference architecture ...

machine learning

deep learning

data analysis

artificial intelligence

Master thesis within Machine Learning

Application and developement

Hello,I am studying for a master's in Human-centered AI at DTU. I am about to write my thesis next spring (starting around the 1st of February) and in that regard, I am exploring what exciting thesis options exist.Through both my bachelor's and master I have done a lot of different kinds of machine learning and I would thus like to find a thesis project within this area. I wish to write a thesis which both has a practical and theoretical aspect. The practical aspect could be a type of product, w...

Machine Learing

Neural Radiance Fields

Proven team

Neural Radiance Fields research and application

Research into expanding neural radiance fields and then applying it to the real world.

We are looking for a project A bachelor project centered around machine learning Specifically something within the field of deep learing, and we welcome you to propose any projects that could benefit from our set of skills. Currently, we have been looking at Neural Radiance Fields (NeRF) and its applications. It is a new technique that enables novel view synthesis from just a few images. This allows you to "fly" around a scene and see it from any direction. Specifically BaRF, Mip-NeRF 360, and I...

1 x Engineering (Artificial Intelligence and Data)

Risk Management

A Cybersecurity Risk-management Approach

NIS2-directive

Research Aim: The aim of the research is to investigate X's cyber risk management approach in relation to implementing and maintaining the NIS2-directive's minimum security measures to ensure high level security in EU....

Reading disorder

Helping regular people understand the life of dyslexic friends and family

A tool for helping relatives and interested parties to understand life with dyslexia

The thesis is currently marked as just 1 student but ideally I will find 1 or 2 more to join me on this endeavour. The core inspiration for this comes from the games and simulations intended to let typical people experience what it's like to have autism. An example of these would be Autismity. Dyslexia is generally treated less severely than for example autism and we already have various tools to aid dyslexic people deal with education and more, so providing a tool, game or simulation for actual...

Online Fraud

Banking Industry

Identity Theft

Combating Identity Theft and Fraud in Online Games

At present time, fraudsters flourishes in online communities. As a result, the banking industry and the Danish police experience a massive number of reports from victims of this type of crime. Dealing with this problem is important so that it can be safe and secure for the individual to shop online....

1 x MSc in Software Design

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Looking for more thesis topic inspiration? Find topic ideas and examples in related research areas below.

19 Engineering & Technology

Interested in machines, algorithms, and structures that shape industries, societies, and our lives? Browse engineering and technology research topics that merge design, creativity, and innovation toward a smarter future.

Engineering & Technology research topics

7 sustainability & environment.

Interested in environmental dynamics and safeguarding our Planet? Explore research topics in environment, sustainability, and climate seeking to tackle climate change, cultivate sustainable practices, and craft greener, healthier solutions.

Sustainability & Environment research topics

2 chemistry.

Interested in our universe's building blocks, unlocking the secrets of chemical compositions and reactions? Explore chemistry research topics that delve into the world of atoms and molecules.

Chemistry research topics

1 mathematics & statistics.

Interested in the language of numbers, equations, and probabilities? Explore mathematical and statistical research topics digging into real-world puzzles that unravel complex data, patterns, and problems.

Mathematics & Statistics research topics

1 medicine & health.

Interested in the complexities of human well-being, from cellular mechanisms to healthcare systems? Explore medicine and health research topics delving into solutions for healthier societies.

Medicine & Health research topics

Interested in the complexities of the living world, from genes to ecosystems? Explore biology research topics that seek to enrich our understanding of medicine, conservation, and of life itself.

Biology research topics

0 astronomy.

Interesting in delving into the celestial mysteries, from stars and galaxies to the universe's grand narrative? Explore astronomy research topics on an astronomical journey to understand our universe's origin and evolution.

Astronomy research topics

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Digital Commons @ USF > College of Engineering > Computer Science and Engineering > Theses and Dissertations

Computer Science and Engineering Theses and Dissertations

Theses/dissertations from 2023 2023.

Refining the Machine Learning Pipeline for US-based Public Transit Systems , Jennifer Adorno

Insect Classification and Explainability from Image Data via Deep Learning Techniques , Tanvir Hossain Bhuiyan

Brain-Inspired Spatio-Temporal Learning with Application to Robotics , Thiago André Ferreira Medeiros

Evaluating Methods for Improving DNN Robustness Against Adversarial Attacks , Laureano Griffin

Analyzing Multi-Robot Leader-Follower Formations in Obstacle-Laden Environments , Zachary J. Hinnen

Secure Lightweight Cryptographic Hardware Constructions for Deeply Embedded Systems , Jasmin Kaur

A Psychometric Analysis of Natural Language Inference Using Transformer Language Models , Antonio Laverghetta Jr.

Graph Analysis on Social Networks , Shen Lu

Deep Learning-based Automatic Stereology for High- and Low-magnification Images , Hunter Morera

Deciphering Trends and Tactics: Data-driven Techniques for Forecasting Information Spread and Detecting Coordinated Campaigns in Social Media , Kin Wai Ng Lugo

Automated Approaches to Enable Innovative Civic Applications from Citizen Generated Imagery , Hye Seon Yi

Theses/Dissertations from 2022 2022

Towards High Performing and Reliable Deep Convolutional Neural Network Models for Typically Limited Medical Imaging Datasets , Kaoutar Ben Ahmed

Task Progress Assessment and Monitoring Using Self-Supervised Learning , Sainath Reddy Bobbala

Towards More Task-Generalized and Explainable AI Through Psychometrics , Alec Braynen

A Multiple Input Multiple Output Framework for the Automatic Optical Fractionator-based Cell Counting in Z-Stacks Using Deep Learning , Palak Dave

On the Reliability of Wearable Sensors for Assessing Movement Disorder-Related Gait Quality and Imbalance: A Case Study of Multiple Sclerosis , Steven Díaz Hernández

Securing Critical Cyber Infrastructures and Functionalities via Machine Learning Empowered Strategies , Tao Hou

Social Media Time Series Forecasting and User-Level Activity Prediction with Gradient Boosting, Deep Learning, and Data Augmentation , Fred Mubang

A Study of Deep Learning Silhouette Extractors for Gait Recognition , Sneha Oladhri

Analyzing Decision-making in Robot Soccer for Attacking Behaviors , Justin Rodney

Generative Spatio-Temporal and Multimodal Analysis of Neonatal Pain , Md Sirajus Salekin

Secure Hardware Constructions for Fault Detection of Lattice-based Post-quantum Cryptosystems , Ausmita Sarker

Adaptive Multi-scale Place Cell Representations and Replay for Spatial Navigation and Learning in Autonomous Robots , Pablo Scleidorovich

Predicting the Number of Objects in a Robotic Grasp , Utkarsh Tamrakar

Humanoid Robot Motion Control for Ramps and Stairs , Tommy Truong

Preventing Variadic Function Attacks Through Argument Width Counting , Brennan Ward

Theses/Dissertations from 2021 2021

Knowledge Extraction and Inference Based on Visual Understanding of Cooking Contents , Ahmad Babaeian Babaeian Jelodar

Efficient Post-Quantum and Compact Cryptographic Constructions for the Internet of Things , Rouzbeh Behnia

Efficient Hardware Constructions for Error Detection of Post-Quantum Cryptographic Schemes , Alvaro Cintas Canto

Using Hyper-Dimensional Spanning Trees to Improve Structure Preservation During Dimensionality Reduction , Curtis Thomas Davis

Design, Deployment, and Validation of Computer Vision Techniques for Societal Scale Applications , Arup Kanti Dey

AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing , Hamza Elhamdadi

Automatic Detection of Vehicles in Satellite Images for Economic Monitoring , Cole Hill

Analysis of Contextual Emotions Using Multimodal Data , Saurabh Hinduja

Data-driven Studies on Social Networks: Privacy and Simulation , Yasanka Sameera Horawalavithana

Automated Identification of Stages in Gonotrophic Cycle of Mosquitoes Using Computer Vision Techniques , Sherzod Kariev

Exploring the Use of Neural Transformers for Psycholinguistics , Antonio Laverghetta Jr.

Secure VLSI Hardware Design Against Intellectual Property (IP) Theft and Cryptographic Vulnerabilities , Matthew Dean Lewandowski

Turkic Interlingua: A Case Study of Machine Translation in Low-resource Languages , Jamshidbek Mirzakhalov

Automated Wound Segmentation and Dimension Measurement Using RGB-D Image , Chih-Yun Pai

Constructing Frameworks for Task-Optimized Visualizations , Ghulam Jilani Abdul Rahim Quadri

Trilateration-Based Localization in Known Environments with Object Detection , Valeria M. Salas Pacheco

Recognizing Patterns from Vital Signs Using Spectrograms , Sidharth Srivatsav Sribhashyam

Recognizing Emotion in the Wild Using Multimodal Data , Shivam Srivastava

A Modular Framework for Multi-Rotor Unmanned Aerial Vehicles for Military Operations , Dante Tezza

Human-centered Cybersecurity Research — Anthropological Findings from Two Longitudinal Studies , Anwesh Tuladhar

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy , Troi André Williams

Human-centric Cybersecurity Research: From Trapping the Bad Guys to Helping the Good Ones , Armin Ziaie Tabari

Theses/Dissertations from 2020 2020

Classifying Emotions with EEG and Peripheral Physiological Data Using 1D Convolutional Long Short-Term Memory Neural Network , Rupal Agarwal

Keyless Anti-Jamming Communication via Randomized DSSS , Ahmad Alagil

Active Deep Learning Method to Automate Unbiased Stereology Cell Counting , Saeed Alahmari

Composition of Atomic-Obligation Security Policies , Yan Cao Albright

Action Recognition Using the Motion Taxonomy , Maxat Alibayev

Sentiment Analysis in Peer Review , Zachariah J. Beasley

Spatial Heterogeneity Utilization in CT Images for Lung Nodule Classication , Dmitrii Cherezov

Feature Selection Via Random Subsets Of Uncorrelated Features , Long Kim Dang

Unifying Security Policy Enforcement: Theory and Practice , Shamaria Engram

PsiDB: A Framework for Batched Query Processing and Optimization , Mehrad Eslami

Composition of Atomic-Obligation Security Policies , Danielle Ferguson

Algorithms To Profile Driver Behavior From Zero-permission Embedded Sensors , Bharti Goel

The Efficiency and Accuracy of YOLO for Neonate Face Detection in the Clinical Setting , Jacqueline Hausmann

Beyond the Hype: Challenges of Neural Networks as Applied to Social Networks , Anthony Hernandez

Privacy-Preserving and Functional Information Systems , Thang Hoang

Managing Off-Grid Power Use for Solar Fueled Residences with Smart Appliances, Prices-to-Devices and IoT , Donnelle L. January

Novel Bit-Sliced In-Memory Computing Based VLSI Architecture for Fast Sobel Edge Detection in IoT Edge Devices , Rajeev Joshi

Edge Computing for Deep Learning-Based Distributed Real-time Object Detection on IoT Constrained Platforms at Low Frame Rate , Lakshmikavya Kalyanam

Establishing Topological Data Analysis: A Comparison of Visualization Techniques , Tanmay J. Kotha

Machine Learning for the Internet of Things: Applications, Implementation, and Security , Vishalini Laguduva Ramnath

System Support of Concurrent Database Query Processing on a GPU , Hao Li

Deep Learning Predictive Modeling with Data Challenges (Small, Big, or Imbalanced) , Renhao Liu

Countermeasures Against Various Network Attacks Using Machine Learning Methods , Yi Li

Towards Safe Power Oversubscription and Energy Efficiency of Data Centers , Sulav Malla

Design of Support Measures for Counting Frequent Patterns in Graphs , Jinghan Meng

Automating the Classification of Mosquito Specimens Using Image Processing Techniques , Mona Minakshi

Models of Secure Software Enforcement and Development , Hernan M. Palombo

Functional Object-Oriented Network: A Knowledge Representation for Service Robotics , David Andrés Paulius Ramos

Lung Nodule Malignancy Prediction from Computed Tomography Images Using Deep Learning , Rahul Paul

Algorithms and Framework for Computing 2-body Statistics on Graphics Processing Units , Napath Pitaksirianan

Efficient Viewshed Computation Algorithms On GPUs and CPUs , Faisal F. Qarah

Relational Joins on GPUs for In-Memory Database Query Processing , Ran Rui

Micro-architectural Countermeasures for Control Flow and Misspeculation Based Software Attacks , Love Kumar Sah

Efficient Forward-Secure and Compact Signatures for the Internet of Things (IoT) , Efe Ulas Akay Seyitoglu

Detecting Symptoms of Chronic Obstructive Pulmonary Disease and Congestive Heart Failure via Cough and Wheezing Sounds Using Smart-Phones and Machine Learning , Anthony Windmon

Toward Culturally Relevant Emotion Detection Using Physiological Signals , Khadija Zanna

Theses/Dissertations from 2019 2019

Beyond Labels and Captions: Contextualizing Grounded Semantics for Explainable Visual Interpretation , Sathyanarayanan Narasimhan Aakur

Empirical Analysis of a Cybersecurity Scoring System , Jaleel Ahmed

Phenomena of Social Dynamics in Online Games , Essa Alhazmi

A Machine Learning Approach to Predicting Community Engagement on Social Media During Disasters , Adel Alshehri

Interactive Fitness Domains in Competitive Coevolutionary Algorithm , ATM Golam Bari

Measuring Influence Across Social Media Platforms: Empirical Analysis Using Symbolic Transfer Entropy , Abhishek Bhattacharjee

A Communication-Centric Framework for Post-Silicon System-on-chip Integration Debug , Yuting Cao

Authentication and SQL-Injection Prevention Techniques in Web Applications , Cagri Cetin

Multimodal Emotion Recognition Using 3D Facial Landmarks, Action Units, and Physiological Data , Diego Fabiano

Robotic Motion Generation by Using Spatial-Temporal Patterns from Human Demonstrations , Yongqiang Huang

A GPU-Based Framework for Parallel Spatial Indexing and Query Processing , Zhila Nouri Lewis

A Flexible, Natural Deduction, Automated Reasoner for Quick Deployment of Non-Classical Logic , Trisha Mukhopadhyay

An Efficient Run-time CFI Check for Embedded Processors to Detect and Prevent Control Flow Based Attacks , Srivarsha Polnati

Force Feedback and Intelligent Workspace Selection for Legged Locomotion Over Uneven Terrain , John Rippetoe

Detecting Digitally Forged Faces in Online Videos , Neilesh Sambhu

Malicious Manipulation in Service-Oriented Network, Software, and Mobile Systems: Threats and Defenses , Dakun Shen

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Home > Engineering > Computer Science > Computer Science Graduate Projects

Computer Science Graduate Projects and Theses

Theses/dissertations from 2023 2023.

High-Performance Domain-Specific Library for Hydrologic Data Processing , Kalyan Bhetwal

Verifying Data Provenance During Workflow Execution for Scientific Reproducibility , Rizbanul Hasan

Remote Sensing to Advance Understanding of Snow-Vegetation Relationships and Quantify Snow Depth and Snow Water Equivalent , Ahmad Hojatimalekshah

Exploring the Capability of a Self-Supervised Conditional Image Generator for Image-to-Image Translation without Labeled Data: A Case Study in Mobile User Interface Design , Hailee Kiesecker

Fake News Detection Using Narrative Content and Discourse , Hongmin Kim

Anomaly Detection Using Graph Neural Network , Bishal Lakha

Sparse Format Conversion and Code Synthesis , Tobi Goodness Popoola

Portable Sparse Polyhedral Framework Code Generation Using Multi Level Intermediate Representation , Aaron St. George

Severity Measures for Assessing Error in Automatic Speech Recognition , Ryan Whetten

Theses/Dissertations from 2022 2022

Improved Computational Prediction of Function and Structural Representation of Self-Cleaving Ribozymes with Enhanced Parameter Selection and Library Design , James D. Beck

Meshfree Methods for PDEs on Surfaces , Andrew Michael Jones

Deep Learning of Microstructures , Amir Abbas Kazemzadeh Farizhandi

Long-Term Trends in Extreme Environmental Events with Changepoint Detection , Mintaek Lee

Structure Aware Smart Encoding and Decoding of Information in DNA , Shoshanna Llewellyn

Towards Making Transformer-Based Language Models Learn How Children Learn , Yousra Mahdy

Ontology-Based Formal Approach for Safety and Security Verification of Industrial Control Systems , Ramesh Neupane

Improving Children's Authentication Practices with Respect to Graphical Authentication Mechanism , Dhanush Kumar Ratakonda

Hate Speech Detection Using Textual and User Features , Rohan Raut

Automated Detection of Sockpuppet Accounts in Wikipedia , Mostofa Najmus Sakib

Characterization and Mitigation of False Information on the Web , Anu Shrestha

Sinusoidal Projection for 360° Image Compression and Triangular Discrete Cosine Transform Impact in the JPEG Pipeline , Iker Vazquez Lopez

Theses/Dissertations from 2021 2021

Training Wheels for Web Search: Multi-Perspective Learning to Rank to Support Children's Information Seeking in the Classroom , Garrett Allen

Fair and Efficient Consensus Protocols for Secure Blockchain Applications , Golam Dastoger Bashar

Why Don't You Act Your Age?: Recognizing the Stereotypical 8-12 Year Old Searcher by Their Search Behavior , Michael Green

Ensuring Consistency and Efficiency of the Incremental Unit Network in a Distributed Architecture , Mir Tahsin Imtiaz

Modeling Real and Fake News Sharing in Social Networks , Abishai Joy

Modeling and Analyzing Users' Privacy Disclosure Behavior to Generate Personalized Privacy Policies , A.K.M. Nuhil Mehdy

Into the Unknown: Exploration of Search Engines' Responses to Users with Depression and Anxiety , Ashlee Milton

Generating Test Inputs from String Constraints with an Automata-Based Solver , Marlin Roberts

A Case Study in Representing Scientific Applications ( GeoAc ) Using the Sparse Polyhedral Framework , Ravi Shankar

Actors for the Internet of Things , Arjun Shukla

Theses/Dissertations from 2020 2020

Towards Unifying Grounded and Distributional Semantics Using the Words-as-Classifiers Model of Lexical Semantics , Stacy Black

Improving Scientist Productivity, Architecture Portability, and Performance in ParFlow , Michael Burke

Polyhedral+Dataflow Graphs , Eddie C. Davis

Improving Spellchecking for Children: Correction and Design , Brody Downs

A Collection of Fast Algorithms for Scalar and Vector-Valued Data on Irregular Domains: Spherical Harmonic Analysis, Divergence-Free/Curl-Free Radial Basis Functions, and Implicit Surface Reconstruction , Kathryn Primrose Drake

Privacy-Preserving Protocol for Atomic Swap Between Blockchains , Kiran Gurung

Unsupervised Structural Graph Node Representation Learning , Mikel Joaristi

Detecting Undisclosed Paid Editing in Wikipedia , Nikesh Joshi

Do You Feel Me?: Learning Language from Humans with Robot Emotional Displays , David McNeill

Obtaining Real-World Benchmark Programs from Open-Source Repositories Through Abstract-Semantics Preserving Transformations , Maria Anne Rachel Paquin

Content Based Image Retrieval (CBIR) for Brand Logos , Enjal Parajuli

A Resilience Metric for Modern Power Distribution Systems , Tyler Bennett Phillips

Theses/Dissertations from 2019 2019

Edge-Assisted Workload-Aware Image Processing System , Anil Acharya

MINOS: Unsupervised Netflow-Based Detection of Infected and Attacked Hosts, and Attack Time in Large Networks , Mousume Bhowmick

Deviant: A Mutation Testing Tool for Solidity Smart Contracts , Patrick Chapman

Querying Over Encrypted Databases in a Cloud Environment , Jake Douglas

A Hybrid Model to Detect Fake News , Indhumathi Gurunathan

Suitability of Finite State Automata to Model String Constraints in Probablistic Symbolic Execution , Andrew Harris

UNICORN Framework: A User-Centric Approach Toward Formal Verification of Privacy Norms , Rezvan Joshaghani

Detection and Countermeasure of Saturation Attacks in Software-Defined Networks , Samer Yousef Khamaiseh

Secure Two-Party Protocol for Privacy-Preserving Classification via Differential Privacy , Manish Kumar

Application-Specific Memory Subsystem Benchmarking , Mahesh Lakshminarasimhan

Multilingual Information Retrieval: A Representation Building Perspective , Ion Madrazo

Improved Study of Side-Channel Attacks Using Recurrent Neural Networks , Muhammad Abu Naser Rony Chowdhury

Investigating the Effects of Social and Temporal Dynamics in Fitness Games on Children's Physical Activity , Ankita Samariya

BullyNet: Unmasking Cyberbullies on Social Networks , Aparna Sankaran

FALCON: Framework for Anomaly Detection In Industrial Control Systems , Subin Sapkota

Investigating Semantic Properties of Images Generated from Natural Language Using Neural Networks , Samuel Ward Schrader

Incremental Processing for Improving Conversational Grounding in a Chatbot , Aprajita Shukla

Estimating Error and Bias of Offline Recommender System Evaluation Results , Mucun Tian

Theses/Dissertations from 2018 2018

Leveraging Tiled Display for Big Data Visualization Using D3.js , Ujjwal Acharya

Fostering the Retrieval of Suitable Web Resources in Response to Children's Educational Search Tasks , Oghenemaro Deborah Anuyah

Privacy-Preserving Genomic Data Publishing via Differential Privacy , Tanya Khatri

Injecting Control Commands Through Sensory Channel: Attack and Defense , Farhad Rasapour

Strong Mutation-Based Test Generation of XACML Policies , Roshan Shrestha

Performance, Scalability, and Robustness in Distributed File Tree Copy , Christopher Robert Sutton

Using DNA For Data Storage: Encoding and Decoding Algorithm Development , Kelsey Suyehira

Detecting Saliency by Combining Speech and Object Detection in Indoor Environments , Kiran Thapa

Theses/Dissertations from 2017 2017

Identifying Restaurants Proposing Novel Kinds of Cuisines: Using Yelp Reviews , Haritha Akella

Editing Behavior Analysis and Prediction of Active/Inactive Users in Wikipedia , Harish Arelli

CloudSkulk: Design of a Nested Virtual Machine Based Rootkit-in-the-Middle Attack , Joseph Anthony Connelly

Predicting Friendship Strength in Facebook , Nitish Dhakal

Privacy-Preserving Trajectory Data Publishing via Differential Privacy , Ishita Dwivedi

Cultivating Community Interactions in Citizen Science: Connecting People to Each Other and the Environment , Bret Allen Finley

Uncovering New Links Through Interaction Duration , Laxmi Amulya Gundala

Variance: Secure Two-Party Protocol for Solving Yao's Millionaires' Problem in Bitcoin , Joshua Holmes

A Scalable Graph-Coarsening Based Index for Dynamic Graph Databases , Akshay Kansal

Integrity Coded Databases: Ensuring Correctness and Freshness of Outsourced Databases , Ujwal Karki

Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display , Yuan Li

The Effects of Pair-Programming in a High School Introductory Computer Science Class , Ken Manship

Towards Automatic Repair of XACML Policies , Shuai Peng

Identification of Unknown Landscape Types Using CNN Transfer Learning , Ashish Sharma

Hand Gesture Recognition for Sign Language Transcription , Iker Vazquez Lopez

Learning to Code Music : Development of a Supplemental Unit for High School Computer Science , Kelsey Wright

Theses/Dissertations from 2016 2016

Identification of Small Endogenous Viral Elements within Host Genomes , Edward C. Davis Jr.

When the System Becomes Your Personal Docent: Curated Book Recommendations , Nevena Dragovic

Security Testing with Misuse Case Modeling , Samer Yousef Khamaiseh

Estimating Length Statistics of Aggregate Fried Potato Product via Electromagnetic Radiation Attenuation , Jesse Lovitt

Towards Multipurpose Readability Assessment , Ion Madrazo

Evaluation of Topic Models for Content-Based Popularity Prediction on Social Microblogs , Axel Magnuson

CEST: City Event Summarization using Twitter , Deepa Mallela

Developing an ABAC-Based Grant Proposal Workflow Management System , Milson Munakami

Phoenix and Hive as Alternatives to RDBMS , Diana Ornelas

Massively Parallel Algorithm for Solving the Eikonal Equation on Multiple Accelerator Platforms , Anup Shrestha

A Certificateless One-Way Group Key Agreement Protocol for Point-to-Point Email Encryption , Srisarguru Sridhar

Dynamic Machine Level Resource Allocation to Improve Tasking Performance Across Multiple Processes , Richard Walter Thatcher

Theses/Dissertations from 2015 2015

Developing an Application for Evolutionary Search for Computational Models of Cellular Development , Nicolas Scott Cornia

Accelerated Radar Signal Processing in Large Geophysical Datasets , Ravi Preesha Geetha

Integrity Coded Databases (ICDB) – Protecting Integrity for Outsourced Databases , Archana Nanjundarao

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Home > College of Natural Sciences > COMPUTERSCI-ENGINEERING > COMPUTERSCI-ENGINEERING-ETD

Computer Science and Engineering Theses, Projects, and Dissertations

Theses/projects/dissertations from 2023 2023.

CLASSIFICATION OF LARGE SCALE FISH DATASET BY DEEP NEURAL NETWORKS , Priyanka Adapa

GEOSPATIAL WILDFIRE RISK PREDICTION USING DEEP LEARNING , Abner Alberto Benavides

HUMAN SUSPICIOUS ACTIVITY DETECTION , Nilamben Bhuva

MAX FIT EVENT MANAGEMENT WITH SALESFORCE , AKSHAY DAGWAR

MELANOMA DETECTION BASED ON DEEP LEARNING NETWORKS , Sanjay Devaraneni

Heart Disease Prediction Using Binary Classification , Virendra Sunil Devare

CLASSIFICATION OF THORAX DISEASES FROM CHEST X-RAY IMAGES , Sharad Jayusukhbhai Dobariya

WEB BASED MANAGEMENT SYSTEM FOR HOUSING SOCIETY , Likhitha Reddy Eddala

Sales and Stock Management System , Rashmika Gaddam Ms

CONTACTLESS FOOD ORDERING SYSTEM , Rishivar Kumar Goli

RESTAURANT MANAGEMENT WEBSITE , Akhil Sai Gollapudi

DISEASE OF LUNG INFECTION DETECTION USING CNN MODEL -BAYESIAN OPTIMIZATION , poojitha gutha

DATA POISONING ATTACKS ON PHASOR MEASUREMENT UNIT DATA , Rutuja Sanjeev Haridas

CRIME MAPPING ANALYSIS USING WEB APPLICATION. , Lavanya Krishnappa

A LONG-TERM FUNDS PREDICTOR BASED ON DEEP LEARNING , SHUIYI KUANG

LIVER SEGMENTATION AND LESION DETECTION IN MEDICAL IMAGES USING A DEEP LEARNING-BASED U-NET MODEL , Kaushik Mahida

PHASOR MEASUREMENT UNIT DATA VISUALIZATION , Nikhila Mandava

TWITTER POLICING , Hemanth Kumar Medisetty

TRANSACTION MANAGEMENT SYSYEM FOR A PUBLISHER , HASSAIN SHAREEF MOHAMMED JR

LOBANGU: AN OPTICAL CHARACTER RECOGNITION RECEIPT MANAGEMENT APP FOR HEALTH CENTER PHARMACIES IN THE D.R.CONGO AND SURROUNDING EASTERN AFRICAN COUNTRIES , Bénis Munganga

PREDICTIVE MODEL FOR CFPB CONSUMER COMPLAINTS , Vyshnavi Nalluri

REVIEW CLASSIFICATION USING NATURAL LANGUAGE PROCESSING AND DEEP LEARNING , Brian Nazareth

Brain Tumor Detection Using MRI Images , Mayur Patel

QUIZ WEB APPLICATION , Dipti Rathod

HYPOTHYROID DISEASE ANALYSIS BY USING MACHINE LEARNING , SANJANA SEELAM

Pillow Based Sleep Tracking Device Using Raspberry Pi , Venkatachalam Seviappan

FINSERV ANDROID APPLICATION , Harsh Piyushkumar Shah

AUTOMATED MEDICAL NOTES LABELLING AND CLASSIFICATION USING MACHINE LEARNING , Akhil Prabhakar Thota

GENETIC PROGRAMMING TO OPTIMIZE PERFORMANCE OF MACHINE LEARNING ALGORITHMS ON UNBALANCED DATA SET , Asitha Thumpati

GOVERNMENT AID PORTAL , Darshan Togadiya

GENERAL POPULATION PROJECTION MODEL WITH CENSUS POPULATION DATA , Takenori Tsuruga

LUNG LESION SEGMENTATION USING DEEP LEARNING APPROACHES , Sree Snigdha Tummala

DETECTION OF PHISHING WEBSITES USING MACHINE LEARNING , Saranya Valleri

Machine Learning for Kalman Filter Tuning Prediction in GPS/INS Trajectory Estimation , Peter Wright

Theses/Projects/Dissertations from 2022 2022

LEARN PROGRAMMING IN VIRTUAL REALITY? A PROJECT FOR COMPUTER SCIENCE STUDENTS , Benjamin Alexander

LUNG CANCER TYPE CLASSIFICATION , Mohit Ramajibhai Ankoliya

HIGH-RISK PREDICTION FOR COVID-19 PATIENTS USING MACHINE LEARNING , Raja Kajuluri

IMPROVING INDIA’S TRAFFIC MANAGEMENT USING INTELLIGENT TRANSPORTATION SYSTEMS , Umesh Makhloga

DETECTION OF EPILEPSY USING MACHINE LEARNING , Balamurugan Murugesan

SOCIAL MOBILE APPLICATION: UDROP , Mahmoud Oraiqat

Improved Sensor-Based Human Activity Recognition Via Hybrid Convolutional and Recurrent Neural Networks , Sonia Perez-Gamboa

College of Education FileMaker Extraction and End-User Database Development , Andrew Tran

DEEP LEARNING EDGE DETECTION IN IMAGE INPAINTING , Zheng Zheng

Theses/Projects/Dissertations from 2021 2021

A General Conversational Chatbot , Vipin Nambiar

Verification System , Paras Nigam

DESKTOP APPLICATION FOR THE PUZZLE BOARD GAME “RUSH HOUR” , Huanqing Nong

Ahmedabad City App , Rushabh Picha

COMPUTER SURVEILLANCE SYSTEM USING WI-FI FOR ANDROID , Shashank Reddy Saireddy

ANDROID PARKING SYSTEM , Vishesh Reddy Sripati

Sentiment Analysis: Stock Index Prediction with Multi-task Learning and Word Polarity Over Time , Yue Zhou

Theses/Projects/Dissertations from 2020 2020

BUBBLE-IN DIGITAL TESTING SYSTEM , Chaz Hampton

FEEDBACK REVIEW SYSTEM USING SENTIMENT ANALYSIS , Vineeth Kukkamalla

WEB APPLICATION FOR MOVIE PERFORMANCE PREDICTION , Devalkumar Patel

Theses/Projects/Dissertations from 2019 2019

REVIEWS TO RATING CONVERSION AND ANALYSIS USING MACHINE LEARNING TECHNIQUES , Charitha Chanamolu

EASY EXAM , SARTHAK DABHI

EXTRACT TRANSFORM AND LOADING TOOL FOR EMAIL , Amit Rajiv Lawanghare

VEHICLE INFORMATION SYSTEM USING BLOCKCHAIN , Amey Zulkanthiwar

Theses/Projects/Dissertations from 2018 2018

USING AUTOENCODER TO REDUCE THE LENGTH OF THE AUTISM DIAGNOSTIC OBSERVATION SCHEDULE (ADOS) , Sara Hussain Daghustani

California State University, San Bernardino Chatbot , Krutarth Desai

ORGANIZE EVENTS MOBILE APPLICATION , Thakshak Mani Chandra Reddy Gudimetla

SOCIAL NETWORK FOR SOFTWARE DEVELOPERS , Sanket Prabhakar Jadhav

VIRTUALIZED CLOUD PLATFORM MANAGEMENT USING A COMBINED NEURAL NETWORK AND WAVELET TRANSFORM STRATEGY , Chunyu Liu

INTER PROCESS COMMUNICATION BETWEEN TWO SERVERS USING MPICH , Nagabhavana Narla

SENSOR-BASED HUMAN ACTIVITY RECOGNITION USING BIDIRECTIONAL LSTM FOR CLOSELY RELATED ACTIVITIES , Arumugam Thendramil Pavai

NEURAL NETWORK ON VIRTUALIZATION SYSTEM, AS A WAY TO MANAGE FAILURE EVENTS OCCURRENCE ON CLOUD COMPUTING , Khoi Minh Pham

EPICCONFIGURATOR COMPUTER CONFIGURATOR AND CMS PLATFORM , IVO A. TANTAMANGO

STUDY ON THE PATTERN RECOGNITION ENHANCEMENT FOR MATRIX FACTORIZATIONS WITH AUTOMATIC RELEVANCE DETERMINATION , hau tao

Theses/Projects/Dissertations from 2017 2017

CHILDREN’S SOCIAL NETWORK: KIDS CLUB , Eiman Alrashoud

MULTI-WAY COMMUNICATION SYSTEM , S. Chinnam

WEB APPLICATION FOR GRADUATE COURSE RECOMMENDATION SYSTEM , Sayali Dhumal

MOBILE APPLICATION FOR ATTENDANCE SYSTEM COYOTE-ATTENDANCE , Sindhu Hari

WEB APPLICATION FOR GRADUATE COURSE ADVISING SYSTEM , Sanjay Karrolla

Custom T-Shirt Designs , Ranjan Khadka

STUDENT CLASS WAITING LIST ENROLLMENT , AISHWARYA LACHAGARI

ANDROID MOBILE APPLICATION FOR HOSPITAL EXECUTIVES , Vihitha Nalagatla

PIPPIN MACHINE , Kiran Reddy Pamulaparthy

SOUND MODE APPLICATION , Sindhuja Pogaku

I2MAPREDUCE: DATA MINING FOR BIG DATA , Vishnu Vardhan Reddy Sherikar

COMPARING AND IMPROVING FACIAL RECOGNITION METHOD , Brandon Luis Sierra

NATURAL LANGUAGE PROCESSING BASED GENERATOR OF TESTING INSTRUMENTS , Qianqian Wang

AUTOMATIC GENERATION OF WEB APPLICATIONS AND MANAGEMENT SYSTEM , Yu Zhou

Theses/Projects/Dissertations from 2016 2016

CLOTH - MODELING, DEFORMATION, AND SIMULATION , Thanh Ho

CoyoteLab - Linux Containers for Educational Use , Michael D. Korcha

PACKET FILTER APPROACH TO DETECT DENIAL OF SERVICE ATTACKS , Essa Yahya M Muharish

DATA MINING: TRACKING SUSPICIOUS LOGGING ACTIVITY USING HADOOP , Bir Apaar Singh Sodhi

Theses/Projects/Dissertations from 2015 2015

APPLY DATA CLUSTERING TO GENE EXPRESSION DATA , Abdullah Jameel Abualhamayl Mr.

Density Based Data Clustering , Rayan Albarakati

Developing Java Programs on Android Mobile Phones Using Speech Recognition , Santhrushna Gande

THE DESIGN AND IMPLEMENTATION OF AN ADAPTIVE CHESS GAME , Mehdi Peiravi

CALIFORNIA STATE UNIVERSITY SAN BERNARDINO WiN GPS , Francisco A. Ron

ESTIMATION ON GIBBS ENTROPY FOR AN ENSEMBLE , Lekhya Sai Sake

A WEB-BASED TEMPERATURE MONITORING SYSTEM FOR THE COLLEGE OF ARTS AND LETTERS , Rigoberto Solorio

ANTICS: A CROSS-PLATFORM MOBILE GAME , Gerren D. Willis

Theses/Projects/Dissertations from 2014 2014

Introducing Non-Determinism to the Parallel C Compiler , Rowen Concepcion

THE I: A CLIENT-BASED POINT-AND-CLICK PUZZLE GAME , Aldo Lewis

Interactive Student Planner Application , NII TETTEH TACKIE YARBOI

ANDROID MOBILE APPLICATION FOR CREST COMMUNITY CHURCH IN RIVERSIDE , Ran Wei

Proton Computed Tomography: Matrix Data Generation Through General Purpose Graphics Processing Unit Reconstruction , micah witt

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Bx Thesis Program

Students in computer science may write a Bx (BA/BS) thesis to complete a major elective (CMSC 29900) and/or as part of their requirements for Computer Science Honors .

The Bx thesis, generally written in the fourth year, should be a substantial research paper. The project should be pursued largely independently, with faculty guidance and input. The thesis should demonstrate competence and scholarship in the chosen area, displaying the ability to understand and synthesize a wide range of readings (beyond material assigned in standard coursework).

Unlike an MA or PhD thesis, however, the Bx thesis need not be primarily an original research project, but rather can report on sufficiently advanced literature and present the student’s personal understanding and evaluation of this literature. The thesis should aim to present some original research, built on the readings, conducted by the student in consultation with a faculty member.

While students may choose to build software as part of their Bx thesis work, software is not a replacement for the required paper.

Bx  – Bachelor of Arts (BA) or Bachelor of Science (BS)

Bx Thesis Program Director – faculty member who oversees the Bx thesis program for the academic year (currently Blase Ur )

Bx Thesis Advisor – faculty member who oversees a student’s work on their Bx thesis

Bx Thesis Reader – faculty member other than the student’s Bx thesis advisor who commits to reading and recommending the thesis for acceptance or rejection

Graduation Quarter (a.k.a. Quarter 3) – the quarter in which a student intends to graduate

Quarter 1 – two quarters prior to the graduation quarter (i.e. Autumn for students who are graduating in Spring, Spring for students graduating in Winter, and Winter for students who are graduating in the Autumn)

Quarter 2 – one quarter prior to the graduation quarter (i.e. Winter for students who are graduating in Spring, Autumn for students graduating in the Winter, and Spring for students who are graduating in the Autumn)

Below are the expected milestones for completing a Bx thesis. Deadlines are at the end of the weeks indicated. Each deadline is the latest time for completing a milestone. To ensure successful completion of a thesis, students are encouraged to complete milestones earlier when possible.

Quarter 1: 1st week

– The student should identify a potential thesis advisor and thesis topic.

Quarter 1: 8th week

– The student must submit a short (2-3 page) thesis proposal, using this proposal form , to their thesis advisor. – The thesis advisor must approve the proposal.

Quarter 1: 9th week

– The student must submit their advisor-approved proposal to the Bx thesis program director.

Quarter 2: 1st week

– The program director will accept, reject, or suggest changes to the proposal.

Quarter 2: 9th week

– The student, in consultation with their thesis advisor, must identify a second faculty member to serve as their Bx thesis reader.

Quarter 3: 5th week

– The student must submit a completed Bx thesis to their advisor and to their reader.

Quarter 3: 7th week

– The thesis advisor and reader must approve the thesis, using this approval form (coming soon). – The advisor must also write a letter recommending the thesis for acceptance. – The reader may write their own letter or simply concur with the thesis advisor’s letter in writing. – The approval form, letters, and completed thesis must be submitted to the Bx thesis program director.

Other Policies

A student who is completing a Bx thesis in computer science may choose to enroll in CMSC 29900 in their graduation quarter, but they are not required to do so.

Students may not receive compensation for research they complete as part of their work for CMSC 29900.

A faculty member in another department may supervise the Bx thesis upon approval of the Bx Thesis Program Director. A student should ask permission from the director before contacting the outside faculty member.

The Computer Science department may accept a thesis used to meet the Bx requirement in another major if the Bx Thesis Program Director deems the thesis to have sufficient computer science content. Students should consult with the relevant parties in both departments by the earliest Bx proposal deadline (or by the end of their third year, if the other program does not state a deadline). A consent form, to be signed by both departmental advisors, is available from the College adviser; it must be completed and returned to the College adviser by the end of Autumn Quarter of the student’s year of graduation.

(Note: Some of the language for this policy is adapted from the Linguistics Department’s guide for BA papers.)

Home > FACULTIES > Computer Science > CSD-ETD

Computer Science Theses and Dissertations

This collection contains theses and dissertations from the Department of Computer Science, collected from the Scholarship@Western Electronic Thesis and Dissertation Repository

Theses/Dissertations from 2024 2024

A Target-Based and A Targetless Extrinsic Calibration Methods for Thermal Camera and 3D LiDAR , Farhad Dalirani

Investigating Tree- and Graph-based Neural Networks for Natural Language Processing Applications , Sudipta Singha Roy

Theses/Dissertations from 2023 2023

Classification of DDoS Attack with Machine Learning Architectures and Exploratory Analysis , Amreen Anbar

Multi-view Contrastive Learning for Unsupervised Domain Adaptation in Brain-Computer Interfaces , Sepehr Asgarian

Improved Protein Sequence Alignments Using Deep Learning , Seyed Sepehr Ashrafzadeh

INVESTIGATING IMPROVEMENTS TO MESH INDEXING , Anurag Bhattacharjee

Algorithms and Software for Oligonucleotide Design , Qin Dong

Framework for Assessing Information System Security Posture Risks , Syed Waqas Hamdani

De novo sequencing of multiple tandem mass spectra of peptide containing SILAC labeling , Fang Han

Local Model Agnostic XAI Methodologies Applied to Breast Cancer Malignancy Predictions , Heather Hartley

A Quantitative Analysis Between Software Quality Posture and Bug-fixing Commit , Rongji He

A Novel Method for Assessment of Batch Effect on single cell RNA sequencing data , Behnam Jabbarizadeh

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs , Taabish Jeshani

Citation Polarity Identification From Scientific Articles Using Deep Learning Methods , Souvik Kundu

Denoising-Based Domain Adaptation Network for EEG Source Imaging , Runze Li

Decoy-Target Database Strategy and False Discovery Rate Analysis for Glycan Identification , Xiaoou Li

DpNovo: A DEEP LEARNING MODEL COMBINED WITH DYNAMIC PROGRAMMING FOR DE NOVO PEPTIDE SEQUENCING , Yizhou Li

Developing A Smart Home Surveillance System Using Autonomous Drones , Chongju Mai

Look-Ahead Selective Plasticity for Continual Learning , Rouzbeh Meshkinnejad

The Two Visual Processing Streams Through The Lens Of Deep Neural Networks , Aidasadat Mirebrahimi Tafreshi

Source-free Domain Adaptation for Sleep Stage Classification , Yasmin Niknam

Data Heterogeneity and Its Implications for Fairness , Ghazaleh Noroozi

Enhancing Urban Life: A Policy-Based Autonomic Smart City Management System for Efficient, Sustainable, and Self-Adaptive Urban Environments , Elham Okhovat

Evaluating the Likelihood of Bug Inducing Commits Using Metrics Trend Analysis , Parul Parul

On Computing Optimal Repairs for Conditional Independence , Alireza Pirhadi

Open-Set Source-Free Domain Adaptation in Fundus Images Analysis , Masoud Pourreza

Migration in Edge Computing , Arshin Rezazadeh

A Modified Hopfield Network for the K-Median Problem , Cody Rossiter

Predicting Network Failures with AI Techniques , Chandrika Saha

Toward Building an Intelligent and Secure Network: An Internet Traffic Forecasting Perspective , Sajal Saha

An Exploration of Visual Analytic Techniques for XAI: Applications in Clinical Decision Support , Mozhgan Salimiparsa

Attention-based Multi-Source-Free Domain Adaptation for EEG Emotion Recognition , Amir Hesam Salimnia

Global Cyber Attack Forecast using AI Techniques , Nusrat Kabir Samia

IMPLEMENTATION OF A PRE-ASSESSMENT MODULE TO IMPROVE THE INITIAL PLAYER EXPERIENCE USING PREVIOUS GAMING INFORMATION , Rafael David Segistan Canizales

A Computational Framework For Identifying Relevant Cell Types And Specific Regulatory Mechanisms In Schizophrenia Using Data Integration Methods , Kayvan Shabani

Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network , Sareh Soltani Nejad

Smartphone Loss Prevention System Using BLE and GPS Technology , Noshin Tasnim

A Hybrid Continual Machine Learning Model for Efficient Hierarchical Classification of Domain-Specific Text in The Presence of Class Overlap (Case Study: IT Support Tickets) , Yasmen M. Wahba

Reducing Negative Transfer of Random Data in Source-Free Unsupervised Domain Adaptation , Anthony Wong

Deep Neural Methods for True/Pseudo- Invasion Classification in Colorectal Polyp Whole-Slide Images , Zhiyuan Yang

Developing a Relay-based Autonomous Drone Delivery System , Muhammad Zakar

Learning Mortality Risk for COVID-19 Using Machine Learning and Statistical Methods , Shaoshi Zhang

Machine Learning Techniques for Improved Functional Brain Parcellation , Da Zhi

Theses/Dissertations from 2022 2022

The Design and Implementation of a High-Performance Polynomial System Solver , Alexander Brandt

Defining Service Level Agreements in Serverless Computing , Mohamed Elsakhawy

Algorithms for Regular Chains of Dimension One , Juan P. Gonzalez Trochez

Towards a Novel and Intelligent e-commerce Framework for Smart-Shopping Applications , Susmitha Hanumanthu

Multi-Device Data Analysis for Fault Localization in Electrical Distribution Grids , Jacob D L Hunte

Towards Parking Lot Occupancy Assessment Using Aerial Imagery and Computer Vision , John Jewell

Potential of Vision Transformers for Advanced Driver-Assistance Systems: An Evaluative Approach , Andrew Katoch

Psychological Understanding of Textual journals using Natural Language Processing approaches , Amirmohammad Kazemeinizadeh

Driver Behavior Analysis Based on Real On-Road Driving Data in the Design of Advanced Driving Assistance Systems , Nima Khairdoost

Solving Challenges in Deep Unsupervised Methods for Anomaly Detection , Vahid Reza Khazaie

Developing an Efficient Real-Time Terrestrial Infrastructure Inspection System Using Autonomous Drones and Deep Learning , Marlin Manka

Predictive Modelling For Topic Handling Of Natural Language Dialogue With Virtual Agents , Lareina Milambiling

Improving Deep Entity Resolution by Constraints , Soudeh Nilforoushan

Respiratory Pattern Analysis for COVID-19 Digital Screening Using AI Techniques , Annita Tahsin Priyoti

Extracting Microservice Dependencies Using Log Analysis , Andres O. Rodriguez Ishida

False Discovery Rate Analysis for Glycopeptide Identification , Shun Saito

Towards a Generalization of Fulton's Intersection Multiplicity Algorithm , Ryan Sandford

An Investigation Into Time Gazed At Traffic Objects By Drivers , Kolby R. Sarson

Exploring Artificial Intelligence (AI) Techniques for Forecasting Network Traffic: Network QoS and Security Perspectives , Ibrahim Mohammed Sayem

A Unified Representation and Deep Learning Architecture for Persuasive Essays in English , Muhammad Tawsif Sazid

Towards the development of a cost-effective Image-Sensing-Smart-Parking Systems (ISenSmaP) , Aakriti Sharma

Advances in the Automatic Detection of Optimization Opportunities in Computer Programs , Delaram Talaashrafi

Reputation-Based Trust Assessment of Transacting Service Components , Konstantinos Tsiounis

Fully Autonomous UAV Exploration in Confined and Connectionless Environments , Kirk P. Vander Ploeg

Three Contributions to the Theory and Practice of Optimizing Compilers , Linxiao Wang

Developing Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach , Wumian Wang

Predicting and Modifying Memorability of Images , Mohammad Younesi

Theses/Dissertations from 2021 2021

Generating Effective Sentence Representations: Deep Learning and Reinforcement Learning Approaches , Mahtab Ahmed

A Physical Layer Framework for a Smart City Using Accumulative Bayesian Machine Learning , Razan E. AlFar

Load Balancing and Resource Allocation in Smart Cities using Reinforcement Learning , Aseel AlOrbani

Contrastive Learning of Auditory Representations , Haider Al-Tahan

Cache-Friendly, Modular and Parallel Schemes For Computing Subresultant Chains , Mohammadali Asadi

Protein Interaction Sites Prediction using Deep Learning , Sourajit Basak

Predicting Stock Market Sector Sentiment Through News Article Based Textual Analysis , William A. Beldman

Improving Reader Motivation with Machine Learning , Tanner A. Bohn

A Black-box Approach for Containerized Microservice Monitoring in Fog Computing , Shi Chang

Visualization and Interpretation of Protein Interactions , Dipanjan Chatterjee

A Framework for Characterising Performance in Multi-Class Classification Problems with Applications in Cancer Single Cell RNA Sequencing , Erik R. Christensen

Exploratory Search with Archetype-based Language Models , Brent D. Davis

Evolutionary Design of Search and Triage Interfaces for Large Document Sets , Jonathan A. Demelo

Building Effective Network Security Frameworks using Deep Transfer Learning Techniques , Harsh Dhillon

A Deep Topical N-gram Model and Topic Discovery on COVID-19 News and Research Manuscripts , Yuan Du

Automatic extraction of requirements-related information from regulatory documents cited in the project contract , Sara Fotouhi

Developing a Resource and Energy Efficient Real-time Delivery Scheduling Framework for a Network of Autonomous Drones , Gopi Gugan

A Visual Analytics System for Rapid Sensemaking of Scientific Documents , Amirreza Haghverdiloo Barzegar

Calibration Between Eye Tracker and Stereoscopic Vision System Employing a Linear Closed-Form Perspective-n-Point (PNP) Algorithm , Mohammad Karami

Fuzzy and Probabilistic Rule-Based Approaches to Identify Fault Prone Files , Piyush Kumar Korlepara

Parallel Arbitrary-precision Integer Arithmetic , Davood Mohajerani

A Technique for Evaluating the Health Status of a Software Module Using Process Metrics , . Ria

Visual Analytics for Performing Complex Tasks with Electronic Health Records , Neda Rostamzadeh

Predictive Model of Driver's Eye Fixation for Maneuver Prediction in the Design of Advanced Driving Assistance Systems , Mohsen Shirpour

A Generative-Discriminative Approach to Human Brain Mapping , Deepanshu Wadhwa

WesternAccelerator：Rapid Development of Microservices , Haoran Wei

A Lightweight and Explainable Citation Recommendation System , Juncheng Yin

Mitosis Detection from Pathology Images , Jinhang Zhang

Theses/Dissertations from 2020 2020

Visual Analytics of Electronic Health Records with a focus on Acute Kidney Injury , Sheikh S. Abdullah

Towards the Development of Network Service Cost Modeling-An ISP Perspective , Yasmeen Ali

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Thesis and Research Topics in Computer Science

Completing a masters Thesis in computer science is the most challenging task faced by research scholars studying in universities all across the world. As computer science is one of the most vast fields opted by research scholars so finding a new thesis topic in computer science becomes more difficult. With each passing day, new and innovative developments are coming out in this era of mechanization. These developments tend to make human life much easier and better. Technology is the forerunner of this new change. Today our life is incomplete without this technology. Cell phones, laptops and all that have become an integral part of our life. Computer Science is the seed to this technical development. There are a number of good topics in computer science for project, thesis, and research for M.Tech and Ph.D. students.

In the field of academics, we need to get rid of obsolete ideas and focus on new innovative topics which are fast spreading their arms among the vast global audience. Computer Science students both in bachelors and in masters are studying the same topics and subjects from the past few years. Students don’t even have knowledge about new masters research topics. For project and thesis work also they are relying on outdated topics. Projects like school management system, library management system etc. are now out of date. Students should shift their focus to latest technologies which are highly in demand these days and future depend upon these. Here is the list of latest topics in Computer Science that you can choose and work for your project work or thesis and research:

List of few latest thesis topics in computer science is below:

• Thesis topics in data mining
• Thesis topics in machine learning
• Thesis topics in digital image processing
• Latest thesis topics in Internet of things (IOT)
• Research topics in Artificial Intelligence
• Networking can be chosen as a  thesis topic in computer science
• Trending thesis topics in cloud computing
• Data aggregation as a  thesis topics  in Big Data
• Research topics  in Software Engineering

Data Warehousing

Data Warehousing is the process of analyzing data for business purposes. Data warehouse store integrated data from multiple sources at a single place which can later be retrieved for making reports. The data warehouse in simple terms is a type of database different and kept isolated from organization’s run-time database. The data in the warehouse is historical data which is helpful in understanding business goals and make decisions for future prospects. It is a relatively new concept and have high growth in future. Data Warehouse provides Online Analytical Processing(OLAP) tools for the systematic and effective study of data in a multidimensional view. Data Warehouse finds its application in the following areas:

• Financial Sector
• Banking Sector
• Retail Services
• Consumer goods
• Manufacturing

So start working on it if you have knowledge of database and data modeling.

INTERNET OF THINGS(IOT)

Internet of Things(IoT)  is a concept of interconnection of various devices, a vehicle to the internet. IOT make use of actuators and sensors for transferring data to and from the devices. This technology is developed for better efficiency and accuracy apart from minimizing human interaction with the devices. The example for this is home heating in some countries when the temperature drops done through motion sensors which automatically detect the weather conditions. Another example for this is the traffic lights which changes its colors depending upon the traffic. Following are the application areas of Internet of Things(IoT):

• Home Automation
• Agriculture
• Transportation
• Environment

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH  TOPICS IN IOT :-

• The secure and energy efficient data routing in the IOT based networks
• The secure channel establishment algorithm for the isolation of misdirection attack in the IOT
• The clock synchronization of IOT devices of energy efficient data communication in IOT
• The adaptive learning scheme to increase fault tolerance of IOT
• Mobility aware energy efficient routing protocol for Internet of Things
• To propose energy efficient multicasting routing protocol for Internet of Things
• The novel scheme to maintain quality of service in internet of Things
• Link reliable and trust aware RPL routing protocol for Internet of Things
• The energy efficient cluster based routing in Internet of Things
• Optimizing Multipath Routing With Guaranteed Fault Tolerance in Internet of Things

Many people are not aware of this concept so you can choose for your project work and learn something new.

Big Data is a term to denote the large volume of data which is complex to handle. The data may be structured or unstructured. Structured data is an organized data while unstructured data is an unorganized data.  Big data  can be examined for the intuition that can give way to better decisions and schematic business moves. The definition of big data is termed in terms of three Vs. These vs are:

• Volume: Volume defines large volume of data from different sources
• Velocity: It refers to the speed with which the data is generated
• Variety: It refers to the varied amount of data both structured and unstructured.

Application areas:

BELOW IS THE LIST OF FEW LATEST AND TRENDING  RESEARCH TOPICS IN BIG DATA :-

• Privacy preserving big data publishing: a scalable k-anonymization approach using MapReduce.
• Nearest Neighbour Classification for High-Speed Big Data Streams Using Spark.
• Efficient and Rapid Machine Learning Algorithms for Big Data and Dynamic Varying Systems.
• Disease Prediction by Machine Learning Over Big Data From Healthcare Communities.
• A Parallel Multi-classification Algorithm for Big Data Using an Extreme Learning Machine.

Thus you can prepare your project report or thesis report on this.

Cloud Computing

Cloud Computing is a comparatively new technology. It is an internet-based service that creates a shared pool of resources for consumers. There are three service models of  cloud computing  namely:

• Software as a Service(SaaS)
• Platform as a Service(PaaS)
• Infrastructure as a Service(IaaS)

Characteristics of cloud computing are:

• On-demand self-service
• Broad network access
• Shared pool of resources
• Scalability
• Measured service

Below is the list of few latest and trending research topics in Cloud Computing :-

• To isolate the virtual side channel attack in cloud computing
• Enhancement in homomorphic encryption for key management and key sharing
• To overcome load balancing problem using weight based scheme in cloud computing
• To apply watermarking technique in cloud computing to enhance cloud data security
• To propose improvement green cloud computing to reduce fault in the network
• To apply stenography technique in cloud computing to enhance cloud data security
• To detect and isolate Zombie attack in cloud computing

The common examples of cloud computing include icloud from Apple, Google-based Services like Google Drive and many more. The field is very demanding and is growing day by day. You can focus on it if you have interest in innovation.

Semantic Web

Semantic Web is also referred to as Web 3.0 and is the next big thing in the field of communication. It is standardized by World Wide Web Consortium(W3C) to promote common data formats and exchange protocols over the web. It is machine-readable information based and is built on XML technology. It is an extension to Web 2.0. In the semantic web, the information is well defined to enable better cooperation between the computers and the people. In the semantic web, the data is interlinked for better understanding. It is different from traditional data sharing technologies.

It can be a good topic for your thesis or project.

MANET stands for mobile ad hoc network. It is an infrastructure-less network with mobile devices connected wirelessly and is self-configuring. It can change locations independently and can link to other devices through a wireless connection. Following are the various types of  MANETS :

• Vehicular ad hoc network(VANET)
• Smartphone ad-hoc network(SPANET)
• Internet-based mobile ad hoc network(iMANET)

You can use various simulation tools to study the functionality and working of MANET like OPNET,  NS2 , NETSIM, NS3 etc.

In MANET there is no need of central hub to receive and send messages. Instead, the nodes directly send packets to each other.

MANET finds its applications in the following areas:

• Environment sensors
• Vehicular ad hoc communication
• Road Safety

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN MANET :-

• Evaluate and propose scheme for the link recovery in mobile ad hoc networks
• To propose hybrid technique for path establishment using bio-inspired techniques in MANET’s
• To propose secure scheme for the isolation of black hole attack in mobile ad hoc networks
• To propose trust based mechanism for the isolation of wormhole attack in mobile ad hoc networks
• The novel approach for the congestion avoidance in mobile ad hoc networks
• To propose scheme for the detection of selective forwarding attack in mobile ad hoc networks
• To propose localization scheme which reduce faults in mobile ad hoc network
• The energy efficient scheme for multicasting routing in wireless ad hoc network
• The scheme for secure localization aided routing in wireless ad hoc networks
• The cross-layer scheme for opportunistic routing in mobile ad hoc networks

Just go for it if you have interest in the field of networking and make a project on it.

Machine Learning

It is also a relatively new concept in the field of computer science and is a technique of guiding computers to act in a certain way without programming. It makes use of certain complex algorithms to receive an input and predict an output for the same. There are three types of learning;

• Supervised learning
• Unsupervised learning
• Reinforcement learning

Machine Learning  is closely related to statistics. If you are good at statistics then you should opt this topic.

Data Mining

Data Mining is the process of identifying and establishing a relationship between large datasets for finding a solution to a problem through analysis of data. There are various tools and techniques in Data Mining which gives enterprises and organizations the ability to predict futuristic trends.  Data Mining  finds its application in various areas of research, statistics, genetics, and marketing. Following are the main techniques used in the process of Data Mining:

• Decision Trees
• Genetic Algorithm
• Induction method
• Artificial Neural Network
• Association

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN DATA MINING :-

• Performance enhancement of DBSCAN density based clustering algorithm in data mining
• The classification scheme for sentiment analysis of twitter data
• To increase accuracy of min-max k-mean clustering in Data mining
• To evaluate and improve apriori algorithm to reduce execution time for association rule generation
• The classification scheme for credit card fraud detection in Data mining
• To propose novel technique for the crime rate prediction in Data Mining
• To evaluate and propose heart disease prediction scheme in Data Mining
• Software defect prediction analysis using machine learning algorithms
• A new data clustering approach for data mining in large databases
• The diabetes prediction technique for Data mining using classification
• Novel Algorithm for the network traffic classification in Data Mining

Advantages of Data Mining

• Data Mining helps marketing and retail enterprises to study customer behavior.
• Organizations into banking and finance business can get information about customer’s historical data and financial activities.
• Data Mining help manufacturing units to detect faults in operational parameters.
• Data Mining also helps various governmental agencies to track record of financial activities to curb on criminal activities.

Disadvantages of Data Mining

• Privacy Issues
• Security Issues
• Information extracted from data mining can be misused
• Artificial Intelligence

Artificial Intelligence is the intelligence shown by  machines  and it deals with the study and creation of intelligent systems that can think and act like human beings. In  Artificial Intelligence , intelligent agents are studied that can perceive its environment and take actions according to its surrounding environment.

Goals of Artificial Intelligence

Following are the main goals of Artificial Intelligence:

• Creation of expert systems
• Implementation of human intelligence in machines
• Problem-solving through reasoning

Application of Artificial Intelligence

Following are the main applications of Artificial Intelligence:

• Expert Systems
• Natural Language Processing
• Artificial Neural Networks
• Fuzzy Logic Systems

Strong AI –  It is a type of artificial intelligence system with human thinking capabilities and can find a solution to an unfamiliar task.

Weak AI –  It is a type of artificial intelligence system specifically designed for a particular task. Apple’s Siri is an example of Weak AI.

Turing Test is used to check whether a system is intelligent or not. Machine Learning is a part of Artificial Intelligence. Following are the types of agents in Artificial Intelligence systems:

• Model-Based Reflex Agents
• Goal-Based Agents
• Utility-Based Agents
• Simple Reflex Agents

Natural Language Processing –  It is a method to communicate with the intelligent systems using human language. It is required to make intelligent systems work according to your instructions. There are two processes under Natural Language Processing – Natural Language Understanding, Natural Language Generation.

Natural Language Understanding involves creating useful representations from the natural language. Natural Language Generation involves steps like Lexical Analysis, Syntactic Analysis, Semantic Analysis, Integration and Pragmatic Analysis to generate meaningful information.

Image Processing

Image Processing is another field in Computer Science and a popular topic for a thesis in Computer Science. There are two types of image processing – Analog and Digital Image Processing. Digital Image Processing is the process of performing operations on digital images using computer-based algorithms to alter its features for enhancement or for other effects. Through Image Processing, essential information can be extracted from digital images. It is an important area of research in computer science. The techniques involved in image processing include transformation, classification, pattern recognition, filtering, image restoration and various other processes and techniques.

Main purpose of Image Processing

Following are the main purposes of  image processing :

• Visualization
• Image Restoration
• Image Retrieval
• Pattern Measurement
• Image Recognition

Applications of Image Processing

Following are the main applications of Image Processing:

• UV Imaging, Gamma Ray Imaging and CT scan in medical field
• Transmission and encoding
• Robot Vision
• Color Processing
• Pattern Recognition
• Video Processing

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN IMAGE PROCESSING :-

• To propose classification technique for plant disease detection in image processing
• The hybrid bio-inspired scheme for edge detection in image processing
• The HMM classification scheme for the cancer detection in image processing
• To propose efficient scheme for digital watermarking of images in image processing
• The propose block wise image compression scheme in image processing
• To propose and evaluate filter based on internal and external features of an image for image de noising
• To improve local mean filtering scheme for de noising of MRI images
• To propose image encryption base d on textural feature analysis and chaos method
• The classification scheme for the face spoof detection in image processing
• The automated scheme for the number plate detection in image processing

Bioinformatics

Bioinformatics is a field that uses various computational methods and software tools to analyze the biological data. In simple words, bioinformatics is the field that uses computer programming for biological studies. It is the current topic of research in computer science and is also a good topic of choice for the thesis. This field is a combination of computer science, biology, statistics, and mathematics. It uses image and signal processing techniques to extract useful information from a large amount of data. Following are the main applications of bioinformatics:

• It helps in observing mutations in the field of genetics
• It plays an important role in text mining and organization of biological data
• It helps to study the various aspects of genes like protein expression and regulation
• Genetic data can be compared using bioinformatics which will help in understanding molecular biology
• Simulation and modeling of DNA, RNA, and proteins can be done using bioinformatics tools

Quantum Computing

Quantum Computing is a computing technique in which computers known as quantum computers use the laws of quantum mechanics for processing information. Quantum Computers are different from digital electronic computers in the sense that these computers use quantum bits known as qubits for processing. A lot of experiments are being conducted to build a powerful quantum computer. Once developed, these computers will be able to solve complex computational problems which cannot be solved by classical computers. Quantum is the current and the latest topic for research and thesis in computer science.

Quantum Computers work on quantum algorithms like Simon’s algorithm to solve problems. Quantum Computing finds its application in the following areas:

The list is incomplete as there are a number of topics to choose from. But these are the trending fields these days. Whether you have any presentation, thesis project or a seminar you can choose any topic from these and prepare a good report.

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Available Theses Topics

If you are interested in a particular topic listed here for a Bachelor or Master thesis, please contact the corresponding person from the table below.

If you are interested in writing a thesis on another (non-listed) topic within the scope of our group or you want to participate in guided research or an interdisciplinary project, write an email to  Mete Ahunbay . Please state your skills and interests and also attach a current CV and a recent grade report . First contact should be established at least one month before registration of the project in order to allow for sufficient time to settle for a suitable topic.

Templates and Information for Creating Theses:

• Thesis Template (latex)
• Slides Template (ppt & latex)
• General Information for Theses

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Theses in the Department of Computer Science

Here you can find important information about theses in the department of computer science. [Photo: Pixabay]

The final thesis (Bachelor or Master) should show that the student is able to work independently on a complex task related to the study program and present it in a scientifically correct manner. It does not necessarily have to be the last module in the degree program, but there are guidelines as to when it can be started at the earliest (see Planning the Thesis).

In our study programs, there is no requirement that the thesis must be registered no later than X months after the last module exam. Nevertheless, please note that the thesis must be completed AND graded by the end of the maximum study period at the latest.

How does everything work around the thesis?

Requirements for the search for a topic.

• A thesis can only be started if at least 120 ECTS have been acquired in the Bachelor, and at least 60 ECTS in the Master. These ECTS must be entered on the transcript of records!
• The examiner of a thesis MUST be a professor of the Department of Computer Science. The examiner issues the topic and gives the final grade for the thesis.
• A second examiner (required for the master thesis) may come from another department / faculty of the University of Stuttgart.
• Often you will be assigned a supervisor who will give you advice and support and whom you can ask anything about your thesis. The supervisor is generally a member of the examiner's staff.
• It is possible to write a thesis in cooperation with a company. However, this is only possible if the examiner agrees. The company can at most take over the supervision, never the assignment of grades. However, since the orientation of the topics that come from companies often differs significantly from what is required as a thesis at the university, such constructs are very rare.

Finding a topic ...

To find a topic, it is best to contact the professors or their staff directly. Please make sure that you have taken courses from the department you are applying to. Otherwise, it may be difficult to work on a specific research topic of the department because you lack the prerequisites in this specific area. It may be a good start to take your own performance review and see what you particularly liked and where you also performed well on exams. These departments are then worth addressing first.

We try to post offers for theses as well as contact persons for the departments in ILIAS in the computer science marketplace.

If, after two to three months of intensive searching , you still have not found a topic, you can apply to the examination board for assignment of a thesis topic along with evidence of your unsuccessful search to date.

Registration of the thesis

It is important to note that you have to register your thesis with the Examinations Office no later than 1 month after starting the thesis (issue of the topic to you).

If a topic has been agreed upon, the secretary of the examiner prepares the computer science-specific contract including the license agreement (and, if applicable, confidentiality and/or language agreement) and hands out these documents to the student for proofreading. If possible, the time for proofreading and, if necessary, follow-up questions should not exceed one week. The contract documents are then signed by the student and returned to the secretary's office. If no publication is desired, the license agreement is crossed out. However, the document must remain with the contract.

At the same time, download the thesis application form from C@mpus. You can find it under the heading "My applications". If you are studying in the Master of Education, in the B.A. in Computer Science or in the B.A. minor in Computer Science, you will not receive this form from C@mpus, but directly from your exam officer. Please enter the following information in the form:

• the topic of the thesis in the original language and in English,
• the name of the examiner,
• the start date,
• sign the document and hand it in to the examiner's office.

The secretariat will have the document countersigned by the examiner and will then hand it back to you or send you a scan of it. You will then forward the document to the examination office as soon as possible. This can be done via the contact form and you can attach the scan or you can bring it personally to the examination office. There, the registration of the work will be entered into the system and confirmed on the form. Afterwards, please inform the examiner's office that the registration has been entered and that the work can now start. If the registration of the work is visible in the system (for the secretary's office), you will receive a copy of the contract.

By the way ...

• Theses can be registered at any time (even outside the exam registration period).
• In connection with the registration of the final thesis, the application for the issuance of the final documents must also be submitted. If you have any questions, please contact the examination office.

If you have any further questions, please contact the program manager or the examination board.

Submission of the thesis

The thesis must be printed and bound in the required number of copies (see contract). The following must be observed:

• For all printed copies, a rigid transparent film should be used as the front cover and, if possible, a black, solid cover at the back.
• The work must not be bound with a ring binding . Any type of adhesive or glue binding is permitted - preferably with a black linen booklet spine.
• The form requirements are summarized here once again.

To ensure that everything is printed, bound and handed in on time, you should collect the required number of covers from the examiner's office approximately 14 days BEFORE handing in your thesis.

In addition to the print copies the followings things have to be submitted:

• one separately printed title page of the thesis and
• the electronic version (pdf) of the thesis and an electronic version of the abstract in txt format. If you are studying in a German-language program and the thesis was written in English, both an English and a German abstract must be submitted. The electronic files can be sent to the examiner and the secretary's office by e-mail, on a stick or on a CD. The code generated by the work, if any, will be handed over separately to the examiner.

All printed copies and the electronic version must be handed in to the examiner's office by the deadline . After the examination by the secretary's office, you will receive the separate title page signed and date-stamped as proof of submission.

Form specifications, templates & links

Here are once again summarized all the notes (in German only)

• Instructions for examiners for the execution of theses
• Instructions for students
• Form specifications
• Template title page
• Template personal statetemt
• Graduation ceremony of the department

What if problems occur?

You forgot the register the thesis.

Subsequent registration of the thesis is possible for a maximum of one month (from the date of topic assignment). After that, this is only possible upon application to the examination board and only if there are valid reasons for which you are not responsible. Otherwise, the thesis will not be evaluated and you will have to look for a new topic.

Aborting the thesis and second attempt

The topic of the thesis can be returned once within the first 2 months of the processing time (Bachelor thesis) or within the first 3 months of the processing time (Master thesis) without a 5.0 being recorded. After that, this is no longer possible and an abandonment leads to a "Not Passed".

The thesis can be repeated once. If you have returned the topic at the first attempt and received a new one, this is no longer possible at the second attempt.

There is no time limit within which the second attempt must be registered. However, the thesis must be passed within the maximum period of study.

In general ...

If problems arise during the processing period that prevent you from devoting yourself to your thesis in a targeted manner, please contact your examiner and the examination board as soon as possible.

Contact person concerning theses

Katrin Schneider

Program Manager, Department Manager & Erasmus Coordinator of the Computer Science Department

• Profile page
• +49 711 685 88520
• Write e-mail

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How to search for Harvard dissertations

• DASH , Digital Access to Scholarship at Harvard, is the university's central, open-access repository for the scholarly output of faculty and the broader research community at Harvard.  Most Ph.D. dissertations submitted from  March 2012 forward  are available online in DASH.
• Check HOLLIS, the Library Catalog, and refine your results by using the   Advanced Search   and limiting Resource  Type   to Dissertations
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Universities Have a Computer-Science Problem

The case for teaching coders to speak French

Listen to this article

Produced by ElevenLabs and News Over Audio (NOA) using AI narration.

Updated at 5:37 p.m. ET on March 22, 2024

Last year, 18 percent of Stanford University seniors graduated with a degree in computer science, more than double the proportion of just a decade earlier. Over the same period at MIT, that rate went up from 23 percent to 42 percent . These increases are common everywhere: The average number of undergraduate CS majors at universities in the U.S. and Canada tripled in the decade after 2005, and it keeps growing . Students’ interest in CS is intellectual—culture moves through computation these days—but it is also professional. Young people hope to access the wealth, power, and influence of the technology sector.

That ambition has created both enormous administrative strain and a competition for prestige. At Washington University in St. Louis, where I serve on the faculty of the Computer Science & Engineering department, each semester brings another set of waitlists for enrollment in CS classes. On many campuses, students may choose to study computer science at any of several different academic outposts, strewn throughout various departments. At MIT, for example, they might get a degree in “Urban Studies and Planning With Computer Science” from the School of Architecture, or one in “Mathematics With Computer Science” from the School of Science, or they might choose from among four CS-related fields within the School of Engineering. This seepage of computing throughout the university has helped address students’ booming interest, but it also serves to bolster their demand.

Another approach has gained in popularity. Universities are consolidating the formal study of CS into a new administrative structure: the college of computing. MIT opened one in 2019. Cornell set one up in 2020. And just last year, UC Berkeley announced that its own would be that university’s first new college in more than half a century. The importance of this trend—its significance for the practice of education, and also of technology—must not be overlooked. Universities are conservative institutions, steeped in tradition. When they elevate computing to the status of a college, with departments and a budget, they are declaring it a higher-order domain of knowledge and practice, akin to law or engineering. That decision will inform a fundamental question: whether computing ought to be seen as a superfield that lords over all others, or just a servant of other domains, subordinated to their interests and control. This is, by no happenstance, also the basic question about computing in our society writ large.

When I was an undergraduate at the University of Southern California in the 1990s, students interested in computer science could choose between two different majors: one offered by the College of Letters, Arts and Sciences, and one from the School of Engineering. The two degrees were similar, but many students picked the latter because it didn’t require three semesters’ worth of study of a (human) language, such as French. I chose the former, because I like French.

An American university is organized like this, into divisions that are sometimes called colleges , and sometimes schools . These typically enjoy a good deal of independence to define their courses of study and requirements as well as research practices for their constituent disciplines. Included in this purview: whether a CS student really needs to learn French.

The positioning of computer science at USC was not uncommon at the time. The first academic departments of CS had arisen in the early 1960s, and they typically evolved in one of two ways: as an offshoot of electrical engineering (where transistors got their start), housed in a college of engineering; or as an offshoot of mathematics (where formal logic lived), housed in a college of the arts and sciences. At some universities, including USC, CS found its way into both places at once.

The contexts in which CS matured had an impact on its nature, values, and aspirations. Engineering schools are traditionally the venue for a family of professional disciplines, regulated with licensure requirements for practice. Civil engineers, mechanical engineers, nuclear engineers, and others are tasked to build infrastructure that humankind relies on, and they are expected to solve problems. The liberal-arts field of mathematics, by contrast, is concerned with theory and abstraction. The relationship between the theoretical computer scientists in mathematics and the applied ones in engineers is a little like the relationship between biologists and doctors, or physicists and bridge builders. Keeping applied and pure versions of a discipline separate allows each to focus on its expertise, but limits the degree to which one can learn from the other.

Read: Programmers, stop calling yourself engineers

By the time I arrived at USC, some universities had already started down a different path. In 1988, Carnegie Mellon University created what it says was one of the first dedicated schools of computer science. Georgia Institute of Technology followed two years later. “Computing was going to be a big deal,” says Charles Isbell, a former dean of Georgia Tech’s college of computing and now the provost at the University of Wisconsin-Madison. Emancipating the field from its prior home within the college of engineering gave it room to grow, he told me. Within a decade, Georgia Tech had used this structure to establish new research and teaching efforts in computer graphics, human-computer interaction, and robotics. (I spent 17 years on the faculty there, working for Isbell and his predecessors, and teaching computational media.)

Kavita Bala, Cornell University’s dean of computing, told me that the autonomy and scale of a college allows her to avoid jockeying for influence and resources. MIT’s computing dean, Daniel Huttenlocher, says that the speed at which computing evolves justifies the new structure.

But the computing industry isn’t just fast-moving. It’s also reckless. Technology tycoons say they need space for growth, and warn that too much oversight will stifle innovation. Yet we might all be better off, in certain ways, if their ambitions were held back even just a little. Instead of operating with a deep understanding or respect for law, policy, justice, health, or cohesion, tech firms tend to do whatever they want . Facebook sought growth at all costs, even if its take on connecting people tore society apart . If colleges of computing serve to isolate young, future tech professionals from any classrooms where they might imbibe another school’s culture and values—engineering’s studied prudence, for example, or the humanities’ focus on deliberation—this tendency might only worsen.

Read: The moral failure of computer scientists

When I raised this concern with Isbell, he said that the same reasoning could apply to any influential discipline, including medicine and business. He’s probably right, but that’s cold comfort. The mere fact that universities allow some other powerful fiefdoms to exist doesn’t make computing’s centralization less concerning. Isbell admitted that setting up colleges of computing “absolutely runs the risk” of empowering a generation of professionals who may already be disengaged from consequences to train the next one in their image. Inside a computing college, there may be fewer critics around who can slow down bad ideas. Disengagement might redouble. But he said that dedicated colleges could also have the opposite effect. A traditional CS department in a school of engineering would be populated entirely by computer scientists, while the faculty for a college of computing like the one he led at Georgia Tech might also house lawyers, ethnographers, psychologists, and even philosophers like me. Huttenlocher repeatedly emphasized that the role of the computing college is to foster collaboration between CS and other disciplines across the university. Bala told me that her college was established not to teach CS on its own but to incorporate policy, law, sociology, and other fields into its practice. “I think there are no downsides,” she said.

Mark Guzdial is a former faculty member in Georgia Tech’s computing college, and he now teaches computer science in the University of Michigan’s College of Engineering. At Michigan, CS wasn’t always housed in engineering—Guzdial says it started out inside the philosophy department, as part of the College of Literature, Science and the Arts. Now that college “wants it back,” as one administrator told Guzdial. Having been asked to start a program that teaches computing to liberal-arts students, Guzdial has a new perspective on these administrative structures. He learned that Michigan’s Computer Science and Engineering program and its faculty are “despised” by their counterparts in the humanities and social sciences. “They’re seen as arrogant, narrowly focused on machines rather than people, and unwilling to meet other programs’ needs,” he told me. “I had faculty refuse to talk to me because I was from CSE.”

In other words, there may be downsides just to placing CS within an engineering school, let alone making it an independent college. Left entirely to themselves, computer scientists can forget that computers are supposed to be tools that help people. Georgia Tech’s College of Computing worked “because the culture was always outward-looking. We sought to use computing to solve others’ problems,” Guzdial said. But that may have been a momentary success. Now, at Michigan, he is trying to rebuild computing education from scratch, for students in fields such as French and sociology. He wants them to understand it as a means of self-expression or achieving justice—and not just a way of making software, or money.

Early in my undergraduate career, I decided to abandon CS as a major. Even as an undergraduate, I already had a side job in what would become the internet industry, and computer science, as an academic field, felt theoretical and unnecessary. Reasoning that I could easily get a job as a computer professional no matter what it said on my degree, I decided to study other things while I had the chance.

I have a strong memory of processing the paperwork to drop my computer-science major in college, in favor of philosophy. I walked down a quiet, blue-tiled hallway of the engineering building. All the faculty doors were closed, although the click-click of mechanical keyboards could be heard behind many of them. I knocked on my adviser’s door; she opened it, silently signed my paperwork without inviting me in, and closed the door again. The keyboard tapping resumed.

The whole experience was a product of its time, when computer science was a field composed of oddball characters, working by themselves, and largely disconnected from what was happening in the world at large. Almost 30 years later, their projects have turned into the infrastructure of our daily lives. Want to find a job? That’s LinkedIn. Keep in touch? Gmail, or Instagram. Get news? A website like this one, we hope, but perhaps TikTok. My university uses a software service sold by a tech company to run its courses. Some things have been made easier with computing. Others have been changed to serve another end, like scaling up an online business.

Read: So much for ‘learn to code’

The struggle to figure out the best organizational structure for computing education is, in a way, a microcosm of the struggle under way in the computing sector at large. For decades, computers were tools used to accomplish tasks better and more efficiently. Then computing became the way we work and live. It became our culture, and we began doing what computers made possible, rather than using computers to solve problems defined outside their purview. Tech moguls became famous, wealthy, and powerful. So did CS academics (relatively speaking). The success of the latter—in terms of rising student enrollments, research output, and fundraising dollars—both sustains and justifies their growing influence on campus.

If computing colleges have erred, it may be in failing to exert their power with even greater zeal. For all their talk of growth and expansion within academia, the computing deans’ ambitions seem remarkably modest. Martial Hebert, the dean of Carnegie Mellon’s computing school, almost sounded like he was talking about the liberal arts when he told me that CS is “a rich tapestry of disciplines” that “goes far beyond computers and coding.” But the seven departments in his school correspond to the traditional, core aspects of computing plus computational biology. They do not include history, for example, or finance. Bala and Isbell talked about incorporating law, policy, and psychology into their programs of study, but only in the form of hiring individual professors into more traditional CS divisions. None of the deans I spoke with aspires to launch, say, a department of art within their college of computing, or one of politics, sociology, or film. Their vision does not reflect the idea that computing can or should be a superordinate realm of scholarship, on the order of the arts or engineering. Rather, they are proceeding as though it were a technical school for producing a certain variety of very well-paid professionals. A computing college deserving of the name wouldn’t just provide deeper coursework in CS and its closely adjacent fields; it would expand and reinvent other, seemingly remote disciplines for the age of computation.

Near the end of our conversation, Isbell mentioned the engineering fallacy, which he summarized like this: Someone asks you to solve a problem, and you solve it without asking if it’s a problem worth solving. I used to think computing education might be stuck in a nesting-doll version of the engineer’s fallacy, in which CS departments have been asked to train more software engineers without considering whether more software engineers are really what the world needs. Now I worry that they have a bigger problem to address: how to make computer people care about everything else as much as they care about computers.

This article originally mischaracterized the views of MIT’s computing dean, Daniel Huttenlocher. He did not say that computer science would be held back in an arts-and-science or engineering context, or that it needs to be independent.