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 210 matching student topics

Displaying 1–12 of 210 results

See it without touching it: low-cost non-contact sensing for our waterways

Many of our most important waterbodies, including reservoirs, lakes, lagoons, wetlands, sedimentation basins, and constructed wetlands, are still monitored using sparse in-water sensors and periodic grab sampling. These methods are costly to maintain, hard to scale across many sites, and often miss spatially variable changes in water quality.Non-contact sensing offers a different approach. Cameras, spectral sensors, radar, thermal imaging, and other sensing modalities can observe water from outside it, reducing fouling, simplifying servicing, improving worker safety, and enabling broader spatial …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Civil and Environmental Engineering

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

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

AI in construction

AI has been impacting businesses and professionals in unprecedented ways. This project will investigate how AI is impacting construction planning, management and execution of construction projects both in positive and negative ways and how Australian construction firms and professionals can better prepare themselves to ride with it.

Study level
PhD
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Explainable AI for medical imaging

AI is increasingly used for interpreting medical images (e.g. MRI, CT, X-ray) in order to diagnose or monitor diseases. We are working on methods that can explain the AI decision and provide supplementary information. For example, if AI detect an abnormality, we want to generate the same scan without the abnormality. Another example is to detect automatically an area that is suspicious just by learning what healthy scans look like.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Development of a machine learning algorithm for high throughput cell response data in drug therapy

High-throughput screening assays are essential for accelerating drug discovery, but current assays often rely on endpoint measurements that do not capture the dynamic response of cells to drug treatment. Machine learning algorithms (MLAs) have the potential to enable real-time, high-throughput monitoring of cell response to drug treatment by analyzing complex datasets generated by multiplexed live-cell assays. This research project aims to develop an MLA for enabling high throughput cell response data in drug treatment. The project will involve three main …

Study level
Honours
Faculty
Faculty of Engineering
School
School of Computer Science
Research centre(s)
Centre for Biomedical Technologies
Centre for Biomedical Technologies

Artificial intelligence (AI) to balance fluctuations of intermittent renewable energy sources

Artificial intelligence (AI) can play a significant role in analyzing and predicting energy consumption and production patterns from renewable sources such as solar and wind (Lyu & Liu 2021). This is particularly important due to the key challenge of intermittency, where major renewable sources for electricity, such as solar and wind, are subject to the inconsistencies of the weather (Watson et al., 2022).In this project, we investigate how AI and machine learning algorithms can optimize smart grids and other components …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Future Enterprise
Energy Transition Centre

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

Cybersecurity for open-source software using machine learning and AI

People are increasingly using open-source software in businesses and industries. These software programs are made by a community of developers and are managed by platforms like PyPI and npm. However, there is a worry about the safety of these programs because hackers add harmful code to compromise security and steal important data. This project explores approaches to detect harmful open-source projects using machine learning and AI.

Study level
Honours
Faculty
Faculty of Science
School
School of Computer Science

The Impact of AI on Leadership Roles and Structures

Examine how the introduction of AI technologies reshapes traditional leadership roles and organisational structures. Investigate the evolving nature of leadership in decentralised, AI-driven decision-making processes and explore how leaders can effectively adapt to new leadership paradigms.

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

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