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 58 matching student topics
Displaying 49–58 of 58 results
Predicting player performance from one format to another in cricket
Identifying talent as early as possible in elite sport is critical. An important component of this is learning about what metrics of performance in lower grades to focus on to help predict performance in the top grade. This project will explore for this research problem for cricket.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Machine learning for understanding and predicting behaviour
Understanding behaviour and predicting events is a core machine learning task, and has many applications in areas including computer vision (to detect or prediction actions in video) and signal processing (to detect events in medical signals).While a large body of research exists exploring these tasks, a number of common challenges persist including:capturing variations in how behaviours or events appear across different subjects, such that predictions can be accurately made for previously unseen subjectsmodelling and incorporating long-term relationships, such as previously …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Green polymer-inorganic composite materials
Composite materials are widely researched and widely used in applications such as aircraft, automobiles, ships, structural components and even the space industry.There is a need to create new composite materials which are environmentally friendly and do not use fossil fuel based products. Moreover, the properties of the composites need to be improved while at the same time minimising the costs involved.Consequently our research group is working on composite materials which not only include inexpensive inorganic fillers from the mining sector …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
Development of a machine learning algorithm for high throughput cell response data in drug therapy
High-throughput screening assays are essential for accelerating drug discovery, but current assays often rely on endpoint measurements that do not capture the dynamic response of cells to drug treatment. Machine learning algorithms (MLAs) have the potential to enable real-time, high-throughput monitoring of cell response to drug treatment by analyzing complex datasets generated by multiplexed live-cell assays. This research project aims to develop an MLA for enabling high throughput cell response data in drug treatment. The project will involve three main …
- Study level
- Honours
- Faculty
- Faculty of Engineering
- School
- School of Computer Science
- Research centre(s)
- Centre for Biomedical Technologies
Centre for Biomedical Technologies
Identifying Indigenous contributions to knowledge
The Australian Census collects data every ten years to reflect who we are as a nation. But the data collected by the Census only tells part of our story.Indigenous people lived in Australia for thousands of years before the arrival of European settlers, accumulating a wealth of knowledge about Australia's land, climate, flora and fauna. Researchers have only begun tapping this knowledge as the basis for modern scientific research.This project will combine machine learning and text-analytics tools to develop a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Analysis of professional squash matches
This project concerns computer vision and statistical analysis of performance in professional level matches in the game of squash.The goal is to use computer vision and existing systems to capture and analyse patterns of play, allowing coaches and professional players to develop strategies to improve performance, to counter particular types of play and even to tailor game plans to attack individual opponents.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Physics-informed reinforcement learning for complex environments, using graph neural networks
Neglecting to incorporate physics information into world models for reinforcement learning leads to reduced adaptability to dynamic and complex environments and overall learning outcomes.In this project, we endeavour to develop and implement learnable models in reinforcement learning (RL) based on graph neural networks (GNNs). These models will integrate object and relation-centric representations to enable accurate predictions, strong generalization, and system identification in complex, dynamical systems. Additionally, we will focus on leveraging extensive world knowledge or physics information to refine representations …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Human-in-the-loop techniques to debug machine learning models
Machine learning models are being deployed in critical domains such as healthcare, education and fintech. The current approach to deploying machine learning models is based on considering a data-centric approach where the models are evaluated using performance measures on a test set. However, the high performance of the model on test data is not indicative of its reliability,An important aspect of reliability is in the understanding of what exactly a machine learning model encodes, and to verify if it learns …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Power efficient computing for statistical machine learning
The carbon footprint of computing globally is estimated to be comparable with that of the aviation industry. With the advent of generative artificial intelligence, there is a growing awareness of this environmental impact both in terms of the carbon footprint and other environmental impacts including e-waste and water consumption, predominantly through the use of power-hungry graphics processing units (GPUs).These are particularly relevant issues to many fields that rely on computationally intensive simulations for data analysis or calibration of statistical machine …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Predicting good sleep using computer science: Can we use machine learning to find out 'what's the best bed?'
In the Westernised world a person typically spends one third of their life in bed, with more time spent sleeping in a bed than in any other single activity. Sleep amount and quality of sleep have a direct impact on mood, behaviour, motor skills and overall quality of life. Yet, despite how important restful sleep is for the body to maintain good health, there is a comparatively small amount of studies evaluating key multi-factorial determinants of restful sleep in non-pathological, …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
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