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 23 matching student topics
Displaying 1–12 of 23 results
Internet of Mobile Energy
The emergence of the two-way communication model and Distributed Energy Sources (DES) is transforming traditional power systems from largely centralised energy production to more decentralised and connected management systems. This is called the 'smart grid'.As the smart grid evolves, electric vehicles (EVs) are emerging as unconventional and highly-disruptive participants in the grid that can add significant benefit and flexibility. Notably, EVs are equipped with a relatively high capacity battery that stores energy to power the vehicle.EV batteries, coupled with the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Making predictions using simulation-based stochastic mathematical models
Stochastic simulation-based models are very attractive to study population-biology, disease transmission, development and disease. These models naturally incorporate randomness in a way that is consistent with experimental measurements that describe natural phenomena.Standard statistical techniques are not directly compatible with data produced by simulation-based stochastic models since the model likelihood function is unavailable. Progress can be made, however, by introducing an auxiliary likelihood function can be formulated, and this auxiliary likelihood function can be used for identifiability analysis, parameter estimation and …
- Study level
- PhD, Master of Philosophy
- 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
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
Predicting alternative states induced by multiple interacting feedbacks: seagrass ecosystems as a case study
This project seeks to explore the complex dynamics that might arise from multiple interacting feedbacks in marine ecosystems, by designing ordinary and/or partial differential equation models of these feedbacks and analysing the steady states and/or temporal dynamics of the proposed model(s).It has been hypothesised that many social and ecological systems exhibit alternative stable states due to feedback processes that keep the ecosystem in one state or the other. The result can be tipping points, which are difficult to predict but …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Explainable AI-enabled predictive analytics
Modern predictive analytics underpinned by AI-enabled learning (such as machine learning, deep learning) techniques has become a key enabler to the automation of data-driven decision making. In the context of process monitoring and forecast, predictive analytics has been applied to making predictions about the future state of a running process instance - for example, which task will be carried out next, when and who will perform the task, when will an ongoing process instance complete, what will be the outcome …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Exploring the value and potential of hyperlocal gift economies
The Australian federal government has committed to achieving net-zero carbon emissions by 2050 to address and reverse the effects of climate change and transition to a circular economy. Achieving net-zero will require a shift in how we use, share and dispose of products, and our relationship to our local communities and planet.In other words, this goal will require an extraordinary shift in the way we ordinarily live. As informal practices of circularity are already happening across Australian neighbourhoods, they have …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
Production of hard carbon for sodium-ion batteries
The transition to renewable energy sources such as solar and wind necessitates efficient and large-scale energy storage solutions. Sodium-ion batteries (SIBs) have emerged as a viable alternative to lithium-ion batteries for grid-scale storage due to the abundance and low cost of sodium. Hard carbon anodes, derived from biomass, offer a sustainable and effective solution for SIBs, providing a pathway to enhance energy storage capabilities and support renewable energy integration.
- Study level
- PhD, Master of Philosophy, Honours
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Agriculture and the Bioeconomy
The pulse of sustainability: Interventions to sustainably increase legume production and consumption
Legume-supported value chains, from production to consumption, provide benefits to people and nature that include improved ecosystem functions and resource use efficiency, as well as farmed animal and human health provisions. Environmental co-benefits of legumes include reduced nitrate leaching, increased food sources for pollinators, a greater structural diversity of farmland, and improved soil fertility. Despite the potential of legumes to improve the sustainability of cropping systems and enhance human health, the production and consumption of legumes in Australia is low.Multiple …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Biology and Environmental Science
- Research centre(s)
- Centre for Agriculture and the Bioeconomy
Efficient Parameter Estimation for Stochastic Simulations
Stochastic simulation-based models are routinely used in many areas of science to describe inherent randomness in many real-world systems. Applications include the study of particle physics, imaging if black holes, biochemical processes, the migration of animals, and the spread of infectious diseases. To apply these models to interpret data requires statistical methods to estimate model parameters.Unfortunately, standard statistical techniques are not capable of analysing data using these models. This is largely due to the model likelihood, the probability of the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Surrogate models for accurate prediction and inference in mathematical biology
High fidelity mathematical models of biological phenomena are often complex and can require long computational runtimes which can make computational inference for parameter estimation intractable. In this project we will overcome this challenge by working with computationally simple low fidelity models and build a simple statistical model of the discrepancy between the high and low fidelity models. This approach provides the best of both worlds: we obtain high accuracy predictions using a computationally cheap model surrogate.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Image-based assessment of atherosclerotic plaque vulnerability: Towards a computational tool for early detection and prediction
Plaque characteristics and local haemodynamic/mechanical forces keep changing during plaque progression and rupture.Quantifying these changes and discovering the progression-stress correlation can improve our understanding of plaque progression/rupture. This will lead to a quantitative assessment tool for early detection of vulnerable plaques and prediction of possible ruptures.Our research project aims to combine medical imaging, computational modelling, phantom experiments and pathological analysis to investigate plaque progression and vulnerability to rupture in both animal models and patients with carotid stenosis.We will identify and …
- 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
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