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 12 matching student topics
Displaying 1–12 of 12 results
Early detection of complications in human pregnancy
Complications of pregnancy, including preterm birth represent the major causes of fetal and neonatal morbidity and mortality and potentially affect childhood and adult susceptibility to both cardiac and metabolic diseases. Early detection of these disorders is, therefore, essential to improve health outcomes for mother and baby.Exosomes are small (40-120 nm), stable, lipid bilayer nanovesicles identified in biological fluids (e.g. in milk, blood, urine and saliva). They contain a diverse array of signalling molecules, including mRNA, microRNA (miR), proteins, lipids and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Explainability of outlier detection methods
Outliers are anomalous observations in a data set that are "outside the norm" of what would be expected. Identifying outliers is an important part of exploratory data analysis and data analysis in general. It is often a challenging problem and calls for advanced methods and approaches, including machine learning-based tools. As methods become more and more complex, their explainability becomes more difficult and more important. This research project will look at all aspects of explainability and explore new approaches and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Automated abnormality detection in endoscopy data
The project focus on developing an artificial intelligence system for automated abnormality detection of endoscopy data. Developing a model for abnormality detection would leverage the capacity to aid medical practitioners in precisely detecting abnormalities by reducing the mistakes that happen via human error. This project will develop an image-based method using deep learning techniques to perform the classification of various abnormalities that can occur within the gastrointestinal tract, such as ulcerative colitis, esophagitis etc.
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
CIIC01 - Detecting cryptic transmission of plasmids
Plasmids are small, often circular pieces of DNA that are commonly found in bacteria. They are a primary vehicle of horizontal gene transfer (the passing of DNA between two different bacteria) and facilitate the sharing of important genes in bacterial communities (such as those for antimicrobial resistance and virulence).Plasmid outbreaks (i.e. the same plasmid transferring between multiple bacteria) have been increasingly identified using whole genome sequencing. However, as plasmids often carry highly repetitive genetic elements, they are usually incompletely assembled …
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
-
Centre for Immunology and Infection Control
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
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
Design, Simulation and Implementation of a Reliable PV Fault Detection Technique
Faults in any elements such as modules, lines, DC-DC converters and DC-AC inverters of photovoltaic (PV) systems can impact the reliability of the system and exacerbate the efficiency. Some other faults such as ground-fault might lead to significant issues such as the risk of fire. Therefore, it is crucial to investigate and detect the faults in the PV system and prescribe the appropriate actions.The supervisory team is looking for passionate students who are keen to conduct an overarching review and …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
-
Centre for Clean Energy Technologies and Practices
Image-based assessment of atherosclerotic plaque vulnerability: Towards a computational tool for early detection and prediction
Plaque characteristics and local haemodynamic/mechanical forces keep changing during plaque progression and rupture.Quantifying these changes and discovering the progression-stress correlation can improve our understanding of plaque progression/rupture. This will lead to a quantitative assessment tool for early detection of vulnerable plaques and prediction of possible ruptures.Our research project aims to combine medical imaging, computational modelling, phantom experiments and pathological analysis to investigate plaque progression and vulnerability to rupture in both animal models and patients with carotid stenosis.We will identify and …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
The insufficient informativeness of measurements in Bayesian detection problems
Shiryaev's Bayesian Quickest Change Detection (QCD) problem is to detect a change in the statistical problems of an observed process. This is an important signal processing problem with application in a diverse range of areas, including:automatic controlquality controlstatisticstarget detection.Recently a critical deficiency in Shiryaev's QCD problem has been identified to occur due to the insufficient informativeness of measurement in low signal-to-noise (SNR) to overcome geometric prior assumption on the change event.These deficiencies are due to the non-ergodic nature of the …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
QIMR05 - Evaluate blood cell free DNA for detection of actionable mutations for advanced lung cancer
LocationQIMR Berghofer, HerstonWe work across multiple different cancer types using a wide range genomics data, including whole-genome, whole-exome, panel sequencing and transcriptome to understand cancer development and treatment of cancer patients.BackgroundLung cancers remain the leading cause of mortality from cancer representing 18% of all cancer’s death, with a 5-year survival of only 10 to 20%. Most lung cancer patients are diagnosed at advanced stages of disease. For the majority of these patients the main method to acquire tumour material for …
- Study level
- Vacation research experience scheme
- School
- School of Biomedical Sciences
Statistical methods for detecting Antarctic ecosystems from space
Satellite images are a frequent and free source of global data which can be used to effectively monitor the environment. We can see how the land is being used, how it’s being changed, what’s there – even where animals are in the landscape. Using these images is essential, particularly for regions where data is expensive to collect or difficult to physically access, like Antarctica. In Antarctica and the sub-Antarctic islands, satellite images can be an easy and quick way to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Culture and corruption risks in local government: the role of technology in detecting fraud
A recent investigation by the Crime and Misconduct Commission found serious fraud and corruption across a number of Queensland city councils. This included inappropriate relationships between the Council and the private sector, in particular property developers and improper use of power and influence for personal benefit by elected councilors.This project investigates how council employees and councillors avoid detection under existing accounting controls, and how they can be strengthened. We will focus on the latest technologies for detecting financial misconduct and …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Business and Law
- School
- School of Accountancy
Contact us
If you have questions about the best options for you, the application process, your research topic, finding a supervisor or anything else, get in touch with us today.