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 431 matching student topics
Displaying 25–36 of 431 results
Scheduling of vessel movements in channel constrained ports
International trade is heavily reliant on maritime transportation which constitutes 80% of total volume. Ports have a significant impact on the efficiency of maritime transportation, with significant delays to vessels observed in accessing or departing ports. These delays can be a result of constraints on wharf capacity, channel capacity, access to tugs and pilots, or a combination of these factors. This project will focus on the development of novel operations research techniques to optimise the efficiency of scheduling vessel movements …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Safe autonomous driving through dense vegetation via advanced perception
One of the remaining challenges to achieve off-road autonomous navigation for mobile robots is the accurate evaluation of vegetated environments, to determine where a robot can safely drive through. To achieve this, robots may use extra sensory modalities compared to humans, such as RADARs that can penetrate through vegetation and see behind it what is not visible to the naked eye. Another option is to physically interact with the environment to 'clear the way'.
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Robot learning for navigation, interaction, and complex tasks
How can robots best learn to navigate in challenging environments and execute complex tasks, such as tidying up an apartment or assist humans in their everyday domestic chores?Often, hand-written architectures are based on complicated state machines that become intractable to design and maintain with growing task complexity. I am interested in developing learning-based approaches that are effective and efficient and scale better to complicated tasks.Especially learning based on semantic information (such as extracted by the research in semantic SLAM above), …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Assessing visual acuity errors in pre-school children (CVER01)
Measuring visual acuity is in preschool children is challenging. In particular, young children will be prone to making mistakes in identifying symbols on eye charts, even when they can see what those symbols are, so called “false negative responses”.This project uses an established vision assessment protocol, EVA testing, and assesses the extent of false negative responses in this task. The protocol assesses the effects of an intervention, pointing to the target on a card, which may decrease false negative responses. …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Clinical Sciences
- Research centre(s)
-
Centre for Vision and Eye Research
Productive reproducible workflows for deep learning-enabled large-scale industry systems
Deep learning is a mainstream to increase the capability of industry systems, particularly for those with massive data input and output. It is seen that many tools are now claimed to be freely available and could facilitate such process of development and deployment significantly with scalability and quality.However, limited attention has been on developing reproducible and productive workflows to identify the tools and their values towards large-scale industry systems. In this project, we will explore how to design such a …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Atmospheric cooling and shading for the Great Barrier Reef
This research sits within the Cooling and Shading Subprogram of the Reef Restoration and Adaptation Program (RRAP).RRAP is an ambitious and innovative R&D effort that places Australia as the leader of coral reef adaptation and restoration science. It is a consortium of Partners, including QUT, dedicated to creating an innovative toolkit of interventions to help the Reef resist, adapt to, and recover from the impacts of climate change. These partners include the Australian Institute of Marine Science, CSIRO, the Great …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
- Research centre(s)
-
Centre for the Environment
Artificial Intelligence for collaborative and intelligent user interfaces
This project seeks to leverage recent advances in machine vision and natural language processing algorithms to support the design and development of knowledge-driven applications that support communication and collaborations with their users.One particular area where this will be investigated is in workplaces for supported employment, that is employment opportunities for people with intellectual disability. One of the questions to address is how machines could respond to what a user shows them in order to assist with decision making in a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Conversational agents that can see
The development of conversational agents, whether as smart home devices, or embedded in mobile devices or social robots, has started in the world of chatbots, with only text available, and then started to build audio features, and finally considering context through sensors and cloud knowledge, as well as offering images in response to a query.However, little attention has been paid to other conversational modalities, such as showing, pointing, or gesturing. The reliance on these is exacerbated in conversation with people …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Evidence-driven policy innovation for urban heat islands
Extreme heatwaves and other extreme weather events are contributing to the fragility of cities and urban infrastructure, which requires urgent attention. Urban heat islands are an exemplar for metropolitan fragile areas, which exacerbate the impact of climate change and global warming on natural hazards, such as wildfires, storms, floods, and droughts, which pose a critical threat to Australian and international communities (Degirmenci et al., 2021). Decision support systems (DSS) can help city planners and policymakers to optimise their decision-making by …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Management
- Research centre(s)
- Centre for Future Enterprise
SleepBeta: co-designing technology with young adults to promote healthy sleep
The aim of the SleepBeta project is collaborate with young adults to promote healthy sleep. Sleep, together with healthy diet and exercise, is a key pillar for a healthy lifestyle. It is important to feeling well and to performing well at school and in university. However, young adults often have unhealthy sleep habits due to stress caused by exams, leisure activities and work commitments, and digital technologies used at night-time. Over the last few years, we explored different sleep and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Identifying corporate tax avoidance
It is not possible to empirically measure, with certainty, a corporation’s level of tax avoidance due to a lack of publicly available information. As such, academic studies that seek to identify determinants, moderators and consequences of corporate tax avoidance, in order to evaluate the equity of the tax system (Callihan, 1994), measure corporate tax avoidance by proxy suggesting a wide variety of calculations.But these calculations have limitations. For example, most proxies measure non conforming (transactions that are accounted for differently …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Accountancy
Automatic Generation of Software Vulnerability Datasets for Machine Learning
In recent years, machine learning has enjoyed profound success in a range of interesting applications such as natural language processing, computer vision and speech recognition. It has been possible mainly due to, in addition to better computing resources, the availability of large amounts of training datasets to these applications. However, in software security research, the lack of large datasets is an open problem that makes it challenging for machine learning to reason about security vulnerabilities found in real-world software. The …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
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