QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.
Found 182 matching student topics
Displaying 37–48 of 182 results
Addressing Australia's affordable housing demand through industrialised construction
Australia is facing an intense housing crisis. Access to affordable housing has sharply declined. Moreover, the average rental vacancy is at historically low, at around 1% in major cities. The Australian government has unveiled ambitious plans to boost housing supply by building thousands and thousands of new homes within the next 10 years. However, the construction industry's capacity is severely constrained to build and supply such as the local industry relies mostly in traditional in-situ construction methods and techniques.This research …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Supply chain vulnerabilities and risks in major infrastructure projects: future proofing Australia's construction supply chain
The repercussions of COVID-19 pandemic, Ukraine war and the conflicts in the Middle East has caused global supply chain disruption. Australia is particularly vulnerable to supply chain disruption due to its unique geographic location, construction environment and dwindling manufacturing base.Significant cost overruns, project delays, productivity decline and compromised quality products and facilities have become norm rather than exception. We have a huge demand for major infrastructures including those needed for the Brisbane 2032 Olympic. Future proofing the construction supply chain …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Resilience of Queensland's housing stocks to natural hazards
With changing climate, rapid population growth/movement, aging population and economic disparity, our housing stocks are increasingly becoming more prone to natural hazards such as flooding, bushfires, extreme heat, and cyclones. We have been witnessing increased frequency of such events and their disproportional impact on housings, related infrastructure, environment, economy, and the livelihood of people.By leveraging UN disaster risk reduction frameworks and other national and Queensland specific frameworks, this research will assess the resilience and vulnerability of public and social housing …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
AI in construction
AI has been impacting businesses and professionals in unprecedented ways. This project will investigate how AI is impacting construction planning, management and execution of construction projects both in positive and negative ways and how Australian construction firms and professionals can better prepare themselves to ride with it.
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Reinforcement learning for fair and ethical AI systems
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
Efficient predictive models using physics-informed machine learning
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 twin in medical or sports context
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
3D scene reconstruction for medical application
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
Explainable AI for medical imaging
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
Habitable water infrastructures
This project explores buildings, public/civic spaces, and landscapes as water infrastructure. Water is integral to human survival; hence, understanding buildings and urban spaces as habitable water infrastructure has the potential to mitigate the effects of the climate crisis, navigate too much water (floods), and too little water (drought), and offer new modes of occupation.With increasing rainfall intensities, floods, rising sea levels, and drought, the pervasive dichotomy between habitable spaces and water infrastructures can no longer hold. The two can't be …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Novel tricuspid valve design and heart pump
Without proper treatment, patients with tricuspid valve regurgitation are at high risk for developing lethal complications, including heart failure or atrial fibrillation (AFib), and disorder heart's rhythm. Currently, open chest surgery is commonly performed to address tricuspid regurgitation. Therefore, there is an urgent need for an alternative approach involving the design of a transcatheter tricuspid valve. This valve is intended to be inserted through minimally invasive techniques, potentially eliminating the need for open chest surgery.This project aims to validate the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Sustainable high performance biocomposites from lignocellulosic biomass for building and automotive applications
Lignocellulosic biomass, such as sugarcane bagasse, is primarily composed of three biopolymers: cellulose, hemicellulose, and lignin. The combination of these components makes lignocellulosic biomass a natural biocomposite material. This PhD project aims to develop innovative biomass processing strategies to convert lignocellulosic biomass into customized biocomposites for building and automotive applications.
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Agriculture and the Bioeconomy
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