Honours and Masters project

Computational modelling of sign languages aims to develop technologies that can serve as means for understanding (i.e., recognising) and producing (i.e., generating) a particular sign language. The objective of this project is to study and contribute to the state-of-the-art in sign language segmentation.

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.

Computational modelling of sign languages aims to develop technologies that can serve as means for understanding (i.e., recognising) and producing (i.e., generating) a particular sign language. The objective of this project is to study and contribute to the state-of-the-art in sign language 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.

Computational modelling of sign languages aims to develop technologies that can serve as means for understanding (i.e., recognising) and producing (i.e., generating) a particular sign language. The objective of this project is to study and contribute to the state-of-the-art in sign language 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.

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.

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.

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.

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.

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

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