Honours and Masters project

This is a research and development project focused on designing a Generative AI tool that supports equitable team practices in software development. The project combines qualitative research, such as persona profile creation, with AI prototyping to explore how GenAI can foster inclusion, improve team dynamics, and accommodate diverse working styles in technical environments. The outcome includes both a functional AI prototype and practical resources for inclusive collaboration.

This project aims to develop a modular and distributed digital twin framework focused on simulating, monitoring, and analysing smart grid data. The framework will represent virtual models of grid components (e.g., loads, meters, nodes) and synchronise them with real-time or simulated data streams using distributed systems principles.

The testbed will support:

This project involves building a system that processes IoMT data(such as heart rate, blood pressure, or glucose levels) from wearable devices to monitor patient health in real time.

The system uses machine learning to detect anomalies and alert healthcare providers or caregivers. It includes data preprocessing, model training, and a simple dashboard for visualization.

Pretrained models

The hidden layers of pretrained foundation models, such as ChatGPT, contain useful and abstract summaries of data. From an information-theoretic perspective, they might compress the data. From a machine learning perspective, they compute useful features of the data. From a statistics perspective, they might be sufficient statistics for a parameter of interest.

Probabilistic models

What is a mixture model?

You may have learned about mixture models in a machine learning or statistics course. A mixture model with K component densities is defined by

The sum of the product of the mixture weights and component densities is guaranteed to be nonnegative and integrates to one, meaning it is a valid probability density.

Gender euphoria addresses times when one's lived experience aligns with their gender identity. This may be personal experiences of one's body, how one is treated by others, or through in-game experiences. Our prior research has developed an understanding of how gender euphoria comes through in video games from first-person research. This project will work toward developing and deploying a questionnaire to study this phenomenon in the wild and analyse the results. 

As games have increased in complexity, so have the worlds in which players find themselves. The automap has become a staple feature of many video games; in some, the players is allowed to edit the map itself during play (e.g., to mark important locations or lay out a course). We know about what games offer players in terms of game maps, but not how players *actually use* those features. This project will collect data on players' cartography activities in games. 

Manual medical report writing is time-consuming and subject to variability. Recent advances in large language models (LLMs) create new opportunities for automating this process. This project explores using LLMs to generate medical reports from a very large dataset, aiming to streamline workflows and support clinical decision-making. Students will work on data preprocessing, model fine-tuning, and performance evaluation, contributing to advances in medical AI.

Australia’s cybersecurity infrastructure, particularly in IoT networks, must be strengthened to meet evolving standards set by international bodies like NIST and the NSA. This project will support Australian organizations in adapting to quantum-safe standards, ensuring the protection of sensitive data and critical system

Leveraging the FLoRA adaptive learning platform, we will conduct a five-phase research program combining experimental studies and advanced trace data analysis. Through time-stamped interaction data, we aim to detect behavioural signals of metacognitive disengagement using machine learning and time-series modeling techniques. These insights will inform the development of adaptive scaffolding tools that encourage students to monitor, evaluate, and adjust their learning strategies when using GenAI.