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 259 matching student topics
Displaying 49–60 of 259 results
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
Reversing Epithelial Mesenchymal Plasticity with Eribulin to Enhance Therapy Response
Epithelial mesenchymal plasticity (EMP) is a highly regulated and powerful cellular process that is fundamental in embryonic development (1), which is hijacked by cancer cells for metastatic progression and therapy resistance in epithelial cancers (2). Eribulin is a microtubule-inhibiting cancer drug discovered in sea sponges and approved for 3rd line therapy in metastatic breast cancer, which was shown to reverse epithelial mesenchymal transition (EMT) (3).We hypothesise that eribulin’s reversal of EMT will sensitise breast cancer cells to other therapies and …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
UAV navigation in GPS denied environments
This PhD project aims to develop a framework for unmanned aerial vehicles (UAV), which optimally balances localisation, mapping and other objectives in order to solve sequential decision tasks under map and pose uncertainty. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining simultaneous localisation and mapping algorithms with partially observable markov decision processes. The project’s expected outcomes will enable UAVs to solve multiple objectives under map and pose uncertainty in GPS-denied environments. This …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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
Flexible thermoelectrics for wearable electronics
Advancements in miniaturisation and integration of electronics have recently stimulated the explosive progress in wearable electronics. With increasing practical needs, our analysis has indicated that the market values of wearable electronics are predicted to boost up to US$50B in 2022 and US$72B in 2026. Currently, conventional batteries have limited applications in wearable electronics due to their requirements of frequent replacement/recharge and extra-maintenance. This is especially true in temperature or pressure sensors in some circumstances such as remote-control smart home systems …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
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
Fine-grained software vulnerability detection using deep learning techniques
Software vulnerability is a major threat to the security of software systems. Thus, the successful prediction of security vulnerability is one of the most effective attack mitigation solutions. Existing approaches for software vulnerability detection (SVD) can be classified into static and dynamic methods. Powered by AI capabilities, especially with the advancement of machine learning techniques, current software has been produced with more sophisticated methodologies and components. This has made the automatic vulnerability proneness prediction even more challenging. Recent research efforts …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Process-data governance patterns
Data is recognised a strategic asset for organisations. There is a growing need to manage the voluminous data an organisation is exposed to in order to use it for decision-making.Of particular significance is process data, which consists of information about the execution of processes. Such information is used to uncover behaviour of processes within an organisation. This brings forth the significance of data governance. Data governance is the exercise of control and authority over management of data. Despite its significance, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Increasing resilience of robotic systems through quickest change detection technology
Future robotics systems are likely to benefit from having an ability to self-diagnose self-failure or the presence of anomalous situations (so that they can switch to fallback or fail-safe modes). Example situations include subtle sensor or actuator failure and cyber security or physical intruder detection.Such low signal-to-noise anomaly detection or self-diagnose problems can be understood using powerful mathematical and statistical tools which QCR has a rich history of advancing through collaboration with industry partners and publication in premium international venues.
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Automating drone traffic management systems
Unmanned Traffic Management (UTM) describes a set of systems, services and procedures that will be developed to manage drone (unmanned aircraft systems/unmanned aerial vehicle/remotely piloted aircraft) operations in and around our cities. From surveillance tasks and package delivery through to passenger transport, UTM will be essentially in ensuring safe and efficient use of our airspace. Essentially, UTM is a new air traffic control system for drones with high levels of automation and advanced decision making and control. This research aims …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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