Honours and Masters project

We explore novel map representations and projections.

This project seeks to explore and trial new map representations for seeing Australian population data sets more effectively.

Whilst Australia has a population of 28 million, nationally it is counted as of the least densely populated in the world due to its size and topography (large areas of semi-arid and desert geography). Yet Australia is one of the world's most urbanised countries with 89% of the population living in a handful of urban areas, mostly with 50KM of the coastline along the east and south coastline. 

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.

In today's digital landscape, cyberattacks are increasingly impacting organisations by disrupting critical services and compromising sensitive data. As these attacks grow in volume and complexity, security teams are increasingly challenged to safeguard sensitive data and maintain operational continuity. Manual efforts of security assessment often led to inconsistent and delayed results, high operational costs, and increased window of opportunity for potential attackers. To effectively mitigate these risks, there is a pressing need for automated security assessment.

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 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.

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.

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.

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.

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:

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