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 7 matching student topics
Displaying 1–7 of 7 results
AI-driven process redesign
This research aims to transform how organisations improve business processes by integrating artificial intelligence with real-time data. Existing process redesign approaches are often static, retrospective, and reliant on manual analysis. While process mining is commonly used to extract insights from historical data, these methods rarely incorporate AI models to support continuous, real-time process adaptation. As a result, they fall short of enabling intelligent, self-adaptive process management.This research addresses these limitations by proposing an AI-assisted, self-adaptive framework that combines historical and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Joint PhD QUT/Münster: Digital innovation in battery energy storage systems
Queensland is a global leader in residential solar photovoltaic adoption, yet battery energy storage uptake is comparatively low, constraining the full potential of decentralised battery energy storage systems (BESS). Similarly, in Germany, battery storage adoption remains limited and regionally concentrated, despite strong national policy support and technological advances in battery manufacturing.This project investigates the behavioural and systemic barriers to BESS adoption and explores how digital solutions can influence energy decisions. It forms part of a broader international collaboration between QUT, …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
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Energy Transition Centre
Improved data analytics for lithium ion batteries
Join the team to be part of an exciting QUT-lead project into materials for Lithium-ion batteries. The project is part of the Federally supported Future Battery Industries - Cooperative Research Centre, which hosts projects all-over the country that are aiming to boost the industry, create clean energy jobs, and enable a sustainable future.In this role you gain access to QUT's one-of-a-kind in Australia, Advanced Battery Facility. At the facility we build lithium batteries in a range of shapes and sizes. …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Centre for Clean Energy Technologies and Practices
Transport big data analytics: Imputing missing data
The missing data problem is often unavoidable for real-world data collection systems because of a variety of factors, such as sensor malfunctioning, maintenance work, transmission errors, and so on. Filling in missing information in a dataset is an important requirement for many machine-learning algorithms that require a complete dataset as input. Data imputation algorithms aim at filling the missing information in a dataset. Many missing data imputation techniques exist in the literature, with applications demonstrated on various types of datasets. …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Human data interaction with big data visual analytics
Our research is seeking to answer the question: 'How can we support human interaction with big data?'We want to integrate the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers. These elements have the capacity to form a powerful knowledge discovery environment. This research will use datasets from the Queensland Government and the QUT Ecoacoustic research group over multiple years. Other big datasets, such as Amazon’s product review dataset, could also be …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Driver engagement and risk in automated driving: Advanced data analytics leveraging driver monitoring systems
The project aims to the explore concept of empathic machines in the context of driver monitoring systems (DMS) and automated driving. The successful candidate will contribute to advancing the understanding of driver engagement, situation awareness, and risk through leveraging advancements in data science techniques on vehicle sensor, DMS, and other related datasets.To apply for this position, please submit the following documents:a cover letter outlining your research interests, relevant qualifications, and motivation to join the Empathic Machines projecta detailed curriculum vitae …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Centre for Future Mobility
Data-driven and process-aware workforce analytics
Modern information systems in today’s organisations record massive amount of event log data capturing the execution of day-to-day core processes within and across organisations. Mining these event log data to drive process analytics and knowledge discovery is known as process mining. To date various process mining techniques have been developed to help extract insights about the actual processes with the ultimate goal to organisations' workforce capability and capacity building.As an important sub-field of process mining, organisational mining focuses on discovering …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
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