Honours and Masters project

This research aims to bridge a critical accessibility gap in digital navigation tools by developing an inclusive, intelligent system that combines map services, street-level imagery, and large language models (LLMs). Current systems often fail to support marginalised users—such as older adults, people with vision impairments, or those with limited mobility—by overlooking nuanced environmental cues such as footpath obstructions, ramp availability, or visibility of building entrances.

Specialised project:

This project applies machine learning and predictive analytics to detect early signs of heart disease using publicly available cardiovascular datasets. Students will clean and analyse health data, apply algorithms such as Decision Trees and Random Forest, and identify key risk factors for heart disease. The project aims to show how data-driven methods can support early intervention and improve patient outcomes.

This project uses machine learning and predictive analytics to group customers based on their shopping habits using publicly available or synthetic transactional datasets. Students will clean and analyse purchase data, apply clustering algorithms such as K-Means and Hierarchical Clustering, and identify common product purchase patterns using association rule mining. The project aims to show how data-driven methods can help businesses better understand customer behaviour and design targeted marketing strategies.

 Title: Health and Social Challenges of Refugee Populations in Australia: A Data-Driven Investigation.

Keywords: Refugees, health outcomes, social challenges, data integration, policy analysis

We will design a multi-agent web agent system (powered by LLMs) capable of understanding natural language user preferences, decomposing complex queries into sub-tasks, and dynamically interacting with heterogeneous online tools and databases (e.g., real estate listings, school ranking data, maps). The goal is to generate recommendations that meet users’ multi-objective constraints. Inspired by recent agentic approaches, this project will explore how autonomous web agents can coordinate and perform sequential web-based operations to solve real-world decision-making problems.

Modern clinical decision-making is constrained by associative models that conflate correlation with causation and overlook interactions among patient factors. This project introduces a unified framework that fuses causal inference with graph neural networks to deliver interpretable, high-precision diagnosis. Using electronic health records, Double Machine Learning isolates causal drivers (e.g., treatment effects, biomarkers) from spurious associations while adjusting for confounders such as socioeconomic status.

Smart glasses that combine mixed reality head-mounted displays with computer vision and natural language understanding, such as the Apple VisionPro or Google XR Glass, have the potential to revolutionise the lives of people with low vision by providing access to information about their environment through augmented vision and audio.

Generating conversational nonverbal behaviour for speakers and listeners, such as hand gestures, facial expressions, and eye-gaze, is of great importance for natural interaction with intelligent agents. The objective of this project is to study and contribute to the state-of-the-art in conversational nonverbal behaviour generation.

This is a research project best suited for students who are independent and willing to take up challenges. It is also a good practice for students who wish to pursue further study at a postgraduate level.

Recognising conversational nonverbal behaviour for speakers and listeners, such as hand gestures, facial expressions, and eye-gaze, is of great importance for natural interaction with intelligent agents. The objective of this project is to study and contribute to the state-of-the-art in conversational nonverbal behaviour recognition.

This is a research project best suited for students who are independent and willing to take up challenges. It is also a good practice for students who wish to pursue further study at a postgraduate level.