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Honours and Masters project

Displaying 1 - 10 of 260 honours projects.


Generative AI for Personalised Feedback in Computing Education

Providing timely, individualised feedback is a persistent challenge in large-scale computing units. This project investigates how Generative AI models can automatically produce pedagogically aligned, rubric-based feedback on student submissions. A prototype system will interface with an LLM API (e.g., OpenAI GPT) and generate structured feedback, which will be evaluated for accuracy, usefulness, and tone against educator benchmarks.

Hybrid Quantum-Classical Optimisation for Combinatorial Problems

Hybrid quantum-classical algorithms such as the Quantum Approximate Optimisation Algorithm (QAOA) and Variational Quantum Eigensolver (VQE) integrate quantum circuits with classical optimisers to solve hard optimisation problems. This project will develop a small-scale hybrid framework in Qiskit to tackle problems like job-shop scheduling or micro-grid energy dispatch, comparing quantum and classical approaches in accuracy and computational efficiency.

Simulation and Analysis of Quantum Search Algorithms under Noise

Quantum algorithms such as Grover’s Search promise quadratic speed-ups over classical search but are sensitive to hardware noise. This project will use Qiskit Aer to model realistic noise channels (decoherence, gate and readout errors) and evaluate their impact on algorithmic performance. By varying circuit depth, qubit count, and noise parameters, the student will identify conditions under which quantum advantage remains achievable and investigate possible error-mitigation strategies.

Heuristic Algorithms for Traveling Salesman and Vehicle Routing Problems

Modern transport and logistics rely on efficient routing to ensure that goods are delivered on time and at minimal cost. Determining the optimal order in which vehicles visit a set of customers is a fundamental challenge in mathematics and computer science. Despite decades of research, this problem remains computationally difficult. To achieve reasonable cost-effectiveness in industry-scale applications, the best-performing methods rely on heuristic and suboptimal solvers. This project will develop new suboptimal algorithms for tackling large instances relevant to practice.

Open source forensic agent

An "agent" or "client" in the context of mobile forensics is the program deployed using an exploit to a mobile device to facilitate extraction of the data from the phone. Some agents can also do other functions like passcode brute-force attacks.

Don’t Miss the Exit: Identifying Critical States in Sequential Decision-Making for Biodiversity

Optimal policies derived from decision-theoretic models such as Markov Decision Processes (MDPs) often prescribe a single “best” action for every state. However, in real-world conservation contexts, managers rarely follow these prescriptions perfectly—due to uncertainty, limited trust, or operational constraints. This project explores how to make optimal policies more useful and interpretable by helping managers identify which states are critical to get right.

Learning Analytics for Concept Map Analysis

This project focuses on the learning analytics of concept maps created by students in individual or collaborative learning settings. The central aim is to analyse the structure, semantics, and evolution of concept maps as representations of students’ knowledge. The project will explore how computational methods can be used to model learning processes and epistemic development through these artefacts.

Depending on your research trajectory, you may investigate questions such as:

General Software Engineering projects -- propose your own project!

If you have any promising idea to work on, and you think I can help you somehow, please feel free to talk to me. 

 

 

here are some examples that previous students proposed:

1. design and implement some interesting software

2. conduct an study related to software performance

3. design a fancy tool to visualize some data

4. design some IDE extension

Privacy-Enhancing Technologies for the Social Good

Privacy-Enhancing Technologies (PETs) are a set of cryptographic tools that allow information processing in a privacy-respecting manner. As an example, imagine we have a user, say Alice, who wants to get a service from a service provider, say SerPro. To provide the service, SerPro requests Alice's private information such as a copy of her passport to validate her identity. In a traditional setting, Alice has no choice but to give away her highly sensitive information. 

Cybersecurity and Cryptography in the Quantum Age

Motivation: The Unseen Bedrock of Modern Life

Cybersecurity and cryptography are the invisible, essential foundations of the modern digital world. Every day, billions of transactions and communications rely on complex mathematical puzzles to ensure confidentiality, integrity, authenticity, privacy and even more security features.