Student topics

Smart use of rich data sets and state-of-the-art models in a central framework provides opportunities to address problems that were previously out of reach. This is particularly true in managing and responding to flood scenarios where an integrated platform can gather forecasted and measured weather and streamflow data and use those data in foresting systems, enabling an integrated visualisation platform for data sharing and real-time decision making.The water engineering research team is developing analytical and visualisation frameworks that can support …

Study level

Honours

Faculty

Faculty of Engineering

School

School of Civil and Environmental Engineering

This project studies how reinforcement learning (RL) can help make automated decisions fairer. Instead of fixing fairness after training, fairness is built into the learning process to create more equal outcomes for different groups. The focus is on important areas like hiring, healthcare, and finance, where biased AI can cause real harm.The aim is to reduce unfair bias while keeping the system accurate, helping create AI that is both effective and socially responsible. You will learn about advanced RL methods, …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

This research explores how advanced physics-informed neural network models can guide the development of simplified yet accurate predictive systems across scientific and engineering domains. The work spans machine learning, computational physics, and applied mathematics, addressing the critical challenge of creating efficient models that maintain physical consistency and predictive reliability.Recent advances in neural operator learning and physics-informed architectures have demonstrated potential for dramatically reducing model complexity while preserving domain-specific knowledge. This research investigates generalisable frameworks for developing simplified predictive models that …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Digital twins are virtual models of physical systems that use real-time data to mirror, simulate, and analyse behaviour. In medical and sports domains, they offer exciting opportunities for innovation.This project focuses on exploring these applications and aims to create digital twins to better understand and improve outcomes in these rapidly evolving fields.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Global concern about urban air quality has been steadily increasing in recent years. However, most studies on the factors influencing air quality have focused on heavily polluted regions or locations in the Northern Hemisphere, where weather patterns, industrial activity, and vegetation differ significantly from those in Australia.Historically, urban areas in Australia have enjoyed relatively good air quality. Yet, rising population density, deforestation, and land use changes are placing increasing pressure on this status. Furthermore, the natural emissions from Australian vegetation …

Study level

Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Earth and Atmospheric Sciences

Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. Standard treatment involves surgical resection of the tumour combined with systemic chemotherapy. While most patients undergo limb-sparing surgery to avoid amputation, this often results in significant morbidity and lifelong complications. These complications stem from the creation of large bone defects, poor healing outcomes, the need for revision surgeries, and long-term prosthetic failureThere is a critical clinical need for regenerative strategies that restore bone integrity and function following …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Health

School

School of Biomedical Sciences

Research centre(s)

Centre for Biomedical Technologies

Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. Despite aggressive treatment involving multi-agent chemotherapy and wide surgical resection, survival outcomes remain poor, with five year survival as low as 13% for patients with metastatic or recurrent disease. Current treatment relies heavily on systemic chemotherapy, which is associated with significant toxicity and long-term side effects, including cardiotoxicity, nephrotoxicity, and impaired growth and fertility. Local recurrence occurs in up to 30% of patients after surgical resection, often …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Health

School

School of Biomedical Sciences

Research centre(s)

Centre for Biomedical Technologies

This project investigates how corporate reporting is shaped by audit quality, board oversight, and emerging ESG assurance practices. With regulatory shifts like the AASB Climate Disclosure Standard and ASSA 5000, the project explores how auditors, boards, and regulators interact to deliver credible disclosures. Cross-country data, especially from Australia, Korea and China, can be used to evaluate assurance frameworks, audit judgement, or ESG strategy governance.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Business and Law

School

School of Accountancy

Research centre(s)

Centre for Future Enterprise

New computer vision methods using machine learning can reconstruct 3D dynamic environments. We are working on medical application to track clinicians, patients body, lesions and tools. Those techniques can be applied for tracking injuries (e.g. wound), providing analytic of operating theatre, and provide guidance for  surgical intervention.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

AI is increasingly used for interpreting medical images (e.g. MRI, CT, X-ray) in order to diagnose or monitor diseases. We are working on methods that can explain the AI decision and provide supplementary information. For example, if AI detect an abnormality, we want to generate the same scan without the abnormality. Another example is to detect automatically an area that is suspicious just by learning what healthy scans look like.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Energy systems are becoming increasingly complex, shaped by fluctuating renewable supply, evolving user behaviour, and dynamic market structures. To navigate this complexity, system dynamics (SD) modelling (Sterman, 2000) offers a powerful lens to understand and influence the behaviour of energy systems over time. By visualising and simulating feedback loops, stock–flow structures, and interdependencies (Fang et al., 2018), SD modelling can help generate actionable insights for designing resilient, adaptive, and user-centred energy solutions.This project explores how SD modelling can support innovation …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Information Systems

Research centre(s)

Energy Transition Centre

This project will be a desktop document review of international policy preferences to food sovereignty.Food sovereignty is the right of peoples to health and culturally appropriate food produced through ecologically sound and sustainable methods, and their right to define their own food and agriculture systems. It incorporates the intergenerational transfer of cultural knowledge through food which is fundamental to maintaining identity, connectedness and traditional practices. The concept has traction in Canada, USA, and Aotearoa, but is only starting to gain …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Health

School

School of Public Health and Social Work