Honours and Minor Thesis projects

Developing quality AI tools for legal texts is the focus of enormous industry, government and
scholarly attention. The potential benefits include greater efficiency, transparency and access to justice.
Moving beyond the hype requires novel transdisciplinary effort to combine IT and Law expertise.
This project engages this challenge by developing a semi-structured knowledge base (KB) and
reasoners for statutes and cases. The project will also construct corresponding training and evaluation
datasets.

To make artwork more accessible to people who are blind or have low vision, museums often offer audio guides or tours. While these options improve accessibility, they do not always provide a complete aesthetic experience.

Autonomous electric vehicle (EV) fleets are emerging as an effective way to solve environmental problems and reduce commute costs in smart cities. Due to the complex spatiotemporal behaviors of passengers and their trips, the unmanaged electric charging demand from EV fleets will significantly impact the existing transportation and electric power infrastructure. Reliable charging networks and charging strategies for EV fleets are the prerequisites to the successful adoption of autonomous EV fleets.

We aim to take the first step to

A lot of decision support systems have been developed to predict or suggest a diagnosis about the health conditions of patients with the aim to assist clinicians in their decisional process. One of the techniques that is proved to present an efficient tool for medical healthcare decision making is Bayesian networks (BNs). BNs are recognized as efficient graphical models that can be used to explain the relationships between variables.

Are you interested in learning Big Data? Big Data is a multi-million industry. This project focuses on processing large data volume, including high velocity stream data.
 

Building a robust and trustworthy (semi-)autonomous agent requires us to build a consistent picture of the state of the world based on the data received from some perception module.

Large Language Models (LLMs) have revolutionized natural language processing (NLP). These models have shown an unprecedented level of knowledge and reasoning, pushing the boundaries of what is achievable in NLP. However, the use of LLMs in the real world still presents numerous difficult challenges and application of LLMs beyond simple API/Prompt calls is very under-explored.

Do you play any classical music instruments, like piano or violin? Would you like to combine your advanced music skills with computer science. This project analyses classical music using computer science techniques.
 

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.

The suitability of a search method for solving an optimisation problem instance depends on the structure of the fitness landscape of that instance. A fitness landscape in the context of combinatorial optimisation problems refers to the search space of possible solutions, the fitness function, and the neighbourhood operator.