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Honours and Minor Thesis projects

Displaying 61 - 70 of 224 honours projects.

Primary supervisor: Benjamin Tag

The global health crisis has put mental health, emotional well-being, and the risks and importance of digital technologies into the global focus. According to a Lancet Commission report, the number of people with mental disorders is increasing in every country of the world and will cost the global economy US$16 trillion by 2030. Emotions have strong implications not only for mental well-being but also for physical health, e.g., down-regulating negative emotions can lower the risk of heart disease.

Primary supervisor: Chunyang Chen

Software testing is a crucial part of the software development process, ensuring that the developed software is of high quality and meets the requirements of the users. However, testing can be a complex and time-consuming task, especially when it comes to testing software in multiple languages. ChatGPT is trained in multiple languages, making it easier for understanding and detect bugs in multilingual software.

Primary supervisor: Chunyang Chen

Product teams always need to conduct a user study with real and targeted users once the product is developed to test the usability and potential bugs in the products; however, this process is always time-consuming and costly. The team may need to find people of different backgrounds, train them, and then spend time with the users when they are doing the study. Moreover, they always need to conduct several rounds of usability tests every time they iterate the product based on the feedback from the previous study or because of the new requirements from product managers.

Primary supervisor: Chunyang Chen

Jupyter notebooks have become a popular platform for data scientists to develop and test their code. However, as the number of code cells and markdown cells increase in a notebook, it can become challenging to maintain code quality and refactoring. While integrated development environments (IDEs) like PyCharm and VSCode have code assistants like Copilot, these features are not widely available in Jupyter notebooks.

Primary supervisor: Chunyang Chen

Recently, large language models (LLM) gained popularity for their emerging powerful capabilities. For example, when given appropriate prompts, they could execute a task following instructions or demonstrations. In this project, we focus on generating chain-of-thought (CoT) prompts, using a codebank filled with basic sketches, to measure LLMs’ ability in automatic debugging.


Primary supervisor: Amin Sakzad

IT Forensics is the art of extracting digital pieces of evidence also known as (aka) artifacts in a forensically sound manner, that is presentable to a court of law. In doing this it covers a range of conceptual levels, from high-level operating systems and computer theory down to computer networking. 

The specific objective(s) of this project is to look at an encrypted piece of data and distinguish what encryption algorithm is used/employed. This would benefit IT Forensics researchers/investigators attacking encrypted volumes, files, folders, etc.

Primary supervisor: Ron Steinfeld

Since the 1990s, researchers have known that commonly-used public-key cryptosystems (such as RSA and Diffie-Hellman systems) could be potentially broken using efficient algorithms running on a special type of computer based on the principles of quantum mechanics, known as a quantum computer. Due to significant recent advances in quantum computing technology, this threat may become a practical reality in the coming years. To mitigate against this threat, new `quantum-safe’ (a.k.a.

Primary supervisor: Alexey Ignatiev

Propositional satisfiability (SAT) is a well-known example of NP-complete problems. Although NP-completeness may be perceived as a drawback, it allows one to solve all the other problems in NP by reducing them to SAT and relying on the power of modern SAT solvers. This is confirmed by a wealth of successful examples of use cases for modern SAT solving, including generalisations and extensions of SAT as well as a wide variety of practical applications in artificial intelligence (AI).

Primary supervisor: Peter Stuckey

Mini-CP is a minimal form of constraint programming solver, designed to allow for easy experimentation and learning. 

One of the most efficient approaches to discrete optimisation solving is using lazy clause generation, which is a hybrid SAT/CP approach to solving problems.  But MiniCP does not currently support this. 

Primary supervisor: Alexey Ignatiev

Given a knowledge base describing the existing background constraints and assumptions about what is possible in the world as well as the prior experience of an autonomous agent on the one hand and probabilistic perception of the current state of the world of the autonomous agent, on the other hand, it is essential to devise and efficiently enumerate the most consistent world models that are likely to be valid under the prior knowledge in order to refine the agent’s up-to-date perception and take the most suitable actions.