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.

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Found 9 matching student topics

Displaying 1–9 of 9 results

Acceptance and adoption of ambient assistive technologies

Vision-based technologies offer new possibilities to assist individuals with cognitive disabilities to live independently. Ambient assistive technologies, such as smart mirrors and social robots, enable new ways to interact at home with AI technologies that can see.How can we ensure the social acceptance and support the adoption of ambient assistive technologies?Technologies that support independent living are about much more than fulfilling a particular task. They alter how people perceive themselves and how they engage with others. Students in this project …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Computer Science

Respectful ambient interactions with vision-based assistive technology

Vision-based technologies offer new possibilities to assist individuals with cognitive disabilities to live independently. Ambient assistive technologies, such as smart mirrors and social robots, enable new ways to interact at home with AI technologies that can see.How can we design respectful ambient interactions that balance assistance and privacy?Students in this project will develop a method and theory of interactive intent for people with cognitive disabilities. The theory will be established through an exploration of the new types of interactions made …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Computer Science

Co-designing ambient assistive technologies

Vision-based technologies offer new possibilities to assist individuals with cognitive disabilities to live independently. Ambient assistive technologies, such as smart mirrors and social robots, enable new ways to interact at home with AI technologies that can see.How can we engage people of all abilities in co-designing ambient assistive technologies?Participation in design is often defined on a spectrum where stakeholders can be categorised as simple informants (surveyed at the start of a project), evaluators (involved in trial iterations of a design), …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Computer Science

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

Enhancing the quality of teaching in Universities: Measuring the impact of professional development and recognition schemes (such as HEA Fellowship) on University Educators and Students

Enhancing the quality of teaching in Universities: Measuring the impact of professional development and recognition schemes (such as HEA Fellowship) on University Educators and Students

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Education

A Human-centric eXplainable Automated Vehicle

CARRS-Q has developed a strong expertise in AV and ADAS, and operate an Automated Vehicle for its research on test track and open roads.We have collected more than 12,000km of sensor data in various Australian conditions, and we are progressing quickly to a broader understanding of safe operation of AV technologies on our roads. We are looking for PhD candidates to progress further on these topics. PhD positions are available for highly motivated domestic and/or international students to work on …

Study level
PhD
Faculty
Faculty of Health
School
School of Psychology and Counselling

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

Educator capability development and recognition in engineering education

This research topic examines educator capability development and recognition in engineering education, with a particular focus on the misalignment between the skills increasingly required of educators and the ways those skills are formally recognised and rewarded in higher education.Building on contemporary scholarship in engineering education and academic career development, the project explores how expectations around teaching quality, digital capability, assessment design, and evidence‑based practice have expanded—while promotion, workload, and recognition frameworks have not always kept pace.The research aims to inform …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering

Implicit representations for place recognition and robot localisation

This project will develop a novel localization pipeline based on implicit map representations. Unlike traditional approaches that use explicit representations like point clouds or voxel grids, the map in our project is represented implicitly in the weights of neural networks such as Neural Radiance Fields (NeRF). You will get a chance to develop a new class of localization algorithms that work directly on the implicit representation, bypassing the costly rendering step from implicit to explicit representation. The designed algorithms will …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

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