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 240 matching student topics
Displaying 37–48 of 240 results
Exploring the accessibility needs of visually impaired peer workers in digital employment support platforms
This project will explore how blind and visually impaired (VI) peer workers use digital platforms in their day to day practice, with the aim of identifying or co-designing a platform that is accessible, JAWS compatible and aligned with the requirements of industry partner Chapter1’s peer-led employment services.
- Study level
- Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Supporting boundary management in young people's AI companion interactions
We invite applications for Honours research within an interdisciplinary research team examining how young people engage with AI companion chatbots (e.g., Character.AI, Replika) and how they manage risks and boundaries in these interactions.AI companions have grown in popularity since the COVID-19 pandemic and are increasingly used by young people seeking connection. This trend raises important concerns, including exposure to harassment, misinformation, and self-harm, as well as the potential impact on human relationships when reliance on AI companions becomes significant.This project …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Physics informed machine learning for energy forecasting
Accurate forecasting is at the heart of many modern industries from energy and transport to retail, supply chains, finance, climate, and health. This research project explores deep learning approaches for time-series forecasting, investigating how modern architectures such as recurrent neural networks, LSTMs, Temporal Convolutional Networks, transformers, and multimodal foundation models can shape the next generation of forecasting systems.The overarching goal is to develop robust, interpretable, and scalable forecasting models that outperform classical methods and work effectively in real-world settings, including …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Energy Transition Centre
Mathematical modelling of brain cancer informed by patient data
In this research project, you will develop a mathematical model, known as an agent-based model, to capture the development of a brain cancer in a patient. The model will then be matched to clinical samples from patients and used to make predictions around treatment efficacy.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Forecast stability and volatility control in decision-centric time series forecasting
This project aims to develop forecasting models that balance accuracy with stability, minimising unnecessary changes in predictions that can disrupt operational decisions.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Energy Transition Centre
Multi-objective optimisation models for forecasting and decision-making in supply chains and energy systems
This PhD project will focus on developing and evaluating multi-objective optimisation models that simultaneously optimise forecasting accuracy and operational decisions in complex systems.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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
Object-centric process mining
Object-Centric Process Mining (OCPM) is an emerging paradigm in process analytics that addresses the limitations of traditional process mining by enabling the analysis of complex, multi-entity business processes. Unlike conventional approaches that focus on a single case notion (e.g., an order or a patient), OCPM allows for the simultaneous tracking and analysis of multiple interacting objects—such as orders, customers, products, and invoices—within a unified process model.This research project explores the theoretical foundations, algorithmic developments, and practical applications of OCPM. It …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Australia's urban and regional atmosphere: investigating influences on air quality
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
Exploring climate-related processes of the Southern Ocean atmosphere
Are you curious about how the Earth's most remote oceans shape our climate? Passionate about data science, scientific discovery, and the polar atmosphere?Join a unique research project that takes you straight into the heart of cutting-edge Antarctic atmospheric science.The Southern Ocean and Antarctic regions are among the fastest-changing and least-understood parts of the planet. Climate models consistently struggle to simulate clouds there and one big reason is aerosols which are microscopic particles that act as seeds for cloud formation and …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
From feedback loops to actionable insights: system dynamics modelling for sustainable energy systems
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
Leveraging AI-driven cognitive computing for energy systems innovation
The transition toward a more sustainable energy system is generating vast volumes of data from distributed sources such as smart meters, energy sensors, and user-end devices. Energy informatics highlights the crucial role of information systems in optimising both energy supply and demand (Watson et al., 2010). In this project, we explore how cognitive computing systems (CCS), integrating artificial intelligence (AI), cognitive psychology, and neurobiology, can strategically transform energy informatics by creating adaptive, explainable, and human-aligned energy solutions.Leveraging advances in CCS …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
-
Energy Transition Centre
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