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 210 matching student topics
Displaying 13–24 of 210 results
Facilitating gaining trust in AI
Artificial intelligence (AI) technologies are automating service delivery in many sectors. Businesses have shown interest in using these technologies for delivering complex services in a way that meet the unique needs of customers. The technology gained more popularity particularly during Covid-19 outbreak, as it helped organisations to become more efficient in service delivery and increased service availability for customers / service applicants. However, gaining managers’ and users’ trust in these systems has always been a significant challenge. Particularly, managers and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Supporting Boundary Management in Young People’s AI Companion Interactions
We invite applications for a PhD position 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 …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Computer Science
Unveiling the explainability imperative in medical AI
As AI systems become increasingly prevalent in medical applications, the need for explainable AI (XAI) has become crucial. This research investigates the critical issue of explainability in medical artificial intelligence (AI) systems. This project investigates methods for improving the interpretability and transparency of AI models used in medical diagnosis, treatment planning, and prognosis prediction. Understanding the reasoning behind AI-driven decisions is essential for building trust among healthcare professionals and ensuring patient safety.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Public Health and Social Work
Leveraging Big Data and AI/ML for Smart Transport Solutions
This PhD position aims to harness the potential of big traffic and mobility data alongside cutting-edge AI/ML algorithms to pioneer innovative solutions for optimizing smart motorways and/or arterial traffic flow. By leveraging these technologies, the project endeavours to develop and test smart algorithms, with the goal of significantly enhancing the efficiency and safety of road networks.Send via email to Prof. Ashish Bhaskar (ashish.bhaskar@qut.edu.au):a brief statement detailing your suitability for the positiona detailed curriculum vitae, including a list of publications, if …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Ethical and Legal Implications of RPA and Enterprise Automation
Examine the ethical and legal implications of RPA/Enterprise Automation adoption in organisations. Research can focus on addressing issues such as data privacy, transparency, accountability, and the impact of RPA/Automation on human employment, culture, and structure.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
-
Centre for Behavioural Economics, Society and Technology
Investigating community advocacy in response to aircraft noise pollution in Brisbane: an ethnographic study
The flight path design and community engagement practices associated with Brisbane Airport have long been criticised for prioritising profit over community wellbeing, leading to excessive aircraft noise pollution. These issues have now amounted to a federal Senate Inquiry and an investigation by the Commonwealth Ombudsman.This PhD research project aims to explore the dynamics between Brisbane Airport and the affected residential communities across more than 220 suburbs, drawing inspiration from a similar study conducted into the social engineering practices of Schiphol …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
- Digital Media Research Centre
Design Lab
Immersive audio data visualisation for better engagement of residential communities exposed to aircraft noise pollution
This PhD project addresses the significant issue of misleading noise data in the context of residential communities exposed to aircraft noise pollution. Despite efforts by authorities to provide noise exposure forecasts and information based on the Australian Noise Exposure Forecast (ANEF) approach, many communities feel misled by the noise contours presented to them. Experiences from previous major development projects at Australian airports have shown a range of problems with relying solely on the ANEF as a noise information tool as …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
-
Design Lab
Basic aircraft collision risk modelling and visualisation
Aircraft collision risk modelling is complex yet key to ensuring safe air transport (both crewed and uncrewed aircraft). Different collision risk models are better suited to different airspace environments which means model comparison and evaluation is an important research problem. This project takes a deeper look into a specific collision risk modelling approach: gas models.
- Study level
- Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
AI-Based Data Analysis on Multiple Imaging Modalities
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Data reasoning to extend domain knowledge in deep learning
A wide variety of companies now use personalized prediction models to improve customer satisfaction, for example, detecting cancer relapses, Detecting Attacks in Networks (e.g., SDN) or understanding Customer Online Shopping Behaviour. However, the dramatic increase in size and complexity of newly generated data from various sources is creating a number of challenges for domain experts to make personalized prediction.For example, early detection of cancer can drastically improve the chance and successful treatment. Recently, supervised deep learning has brought breakthroughs in …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
AI, data, and mathematical thinking in education
This project explores how emerging technologies, including artificial intelligence, influence mathematical thinking, teaching, and learning. It focuses on how students and teachers engage with data-rich and AI-supported environments.The project aligns with ongoing work in quantitative reasoning, modelling, and educational innovation, including research on adaptive learning technologies.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Advanced maintenance of railways
Effective maintenance of railway infrastructure is crucial for safe and comfortable transportation. Rail maintainers currently use a combination of time-based (scheduled) and condition-based approaches to balance the costs and benefits of inspections and maintenance.This project aims to enable advanced maintenance by advanced analysis of degradation patterns, establishment of new predictive models, and development of novel inspection and maintenance optimisation methods to efficiently allocate resources.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
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