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 3 matching student topics

Displaying 1–3 of 3 results

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 Teacher Education and Leadership

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

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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