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 18 matching student topics
Displaying 13–18 of 18 results
Light, circadian rhythms and Parkinson’s disease
Up to 98% of patients with Parkinson’s Disease (PD) have non-motor symptoms (Poewe et al. Nature Rev Dis 2017, 3: 17013) and of those, circadian and sleep disorders are the most common (for review, Gros & Videnovic. 2020, Clin Geriatr Med 36: 119). These symptoms become increasingly prevalent during the course of PD and are key determinants affecting quality of life, advancement of overall disability and placement in nursing homes (Shapira et al. Nat Rev Neurosci 2017,18:435). Circadian and sleep …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Digital Leadership Competencies for AI Adoption
Identify the specific competencies and skills that leaders need to effectively lead AI adoption initiatives in organisations. Research can focus on areas such as data literacy, AI literacy, critical thinking, decision-making, and the ability to manage and interpret AI-driven insights. Develop frameworks for assessing and developing these competencies in leaders.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
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Centre for Behavioural Economics, Society and Technology
Understanding local government artificial intelligence policy landscape
Artificial intelligence (AI) is driving transformation across all areas of society today. An umbrella term encompassing a range of technologies both sophisticated and simple that are used to make predictions, inferences, recommendations, or decisions with data. AI is used in many products and services that people use, interact with, or are impacted by every day. It already in place of local government and assisting government officials in providing services effectively and conduct their activities more efficiently to the public. The …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Investigating the application of sustainable AI practices in construction
The construction industry plays a vital role in the global economy and there is a growing interest in utilising artificial intelligence (AI) to improve its productivity and efficiency. Despite the industry's significant contribution to the economy, it has faced challenges such as large cost overruns, extended schedules, and quality concerns. Nevertheless, AI is making significant strides to remove these issues by revolutionising various aspects of the construction industry. This is evident from enhancing project planning and design to improving construction …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
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
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Drone and satellite Artificial Intelligence
Satellite and drone/UAV data has a great potential to provide large-scale analytics for many domain applications. However, the wide range of data of diverse nature (e.g., optical vs. SAR, high-resolution vs. wide-coverage, mono- vs. hyper-spectral, 2-D vs. 3-D) also poses significant challenges for analytics.Deep learning holds great promise to deal with these tasks. While the number of research in this area is increasing, there still exists challenges such as co-learning of multimodal data, limited data annotation, and uncertainty in the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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