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 8 matching student topics
Displaying 1–8 of 8 results
Strengthening security for cloud computing applications
In today's digital landscape, applications are increasingly being deployed on cloud platforms, offering benefits such as streamlined management and cost-effectiveness. However, even with the efforts of cloud providers to deliver reliable services, the risk of runtime failures and faults still exists. This project aims to address this challenge by exploring innovative approaches to detect and mitigate errors that occur during the operation of cloud-based applications. By proactively identifying and resolving runtime issues, we can enhance the overall performance, reliability, and …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Australian experiences of algorithmic culture on TikTok
Join a world-leading research team examining how recommender systems are shaping personalised and shared experiences of algorithmic culture in Australia. The project is focused on TikTok and engages with both professional TikTok creators and users using innovative computational and traditional research approaches.The empirical work is structured into three streams:In the Platform Stream we observe the type of content TikTok recommends on the least-personalised version of the platform, to create a close-to-generic baseline of the Australian experience of algorithmic culture on …
- Study level
- PhD
- School
- School of Communication
- Research centre(s)
- Digital Media Research Centre
Big data analysis to aid ecological research
We're looking for multiple students to help us answer the question: 'How can we utilise information technology to aid ecological research?'Sensor networks bring ecologists and pattern recognition researchers together to make some applications possible. These applications include assessing risks from potential bird collisions, unobtrusive observations (where the presence of humans changes some animal behaviours) and studying spatial and temporal variation in biological processes.With a significant amount of data being collected from these applications, processing and mining this data is challenging. …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Enabling effective novice-expert interactions: co-designing immersive systems for complex remote data analysis
This student research topic focuses on exploring and developing immersive systems that facilitate interactions between novice and expert users in the context of complex remote data analysis. The goal is to design and prototype innovative solutions that enhance the collaboration, learning, and training aspects of data analysis tasks.The research will involve investigating various immersive technologies and their potential application in bridging the gap between novice and expert users, enabling effective knowledge transfer and skill acquisition.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
AI-Based Data Analysis on Multiple Imaging Modalities
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Data reasoning to extend domain knowledge in deep learning
A wide variety of companies now use personalized prediction models to improve customer satisfaction, for example, detecting cancer relapses, Detecting Attacks in Networks (e.g., SDN) or understanding Customer Online Shopping Behaviour. However, the dramatic increase in size and complexity of newly generated data from various sources is creating a number of challenges for domain experts to make personalized prediction.For example, early detection of cancer can drastically improve the chance and successful treatment. Recently, supervised deep learning has brought breakthroughs in …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Prostate cancer transcriptomics (Honours and Master of Philosophy)
At the Australian Prostate Cancer Research Centre QLD, we are interested in the cellular adaptive response processes leading to therapy resistance in advanced prostate cancer.A focus area of our research is studying the transcriptome changes in prostate cancer cell lines, xenograft models and patient samples using RNA sequencing technologies.By integrating our large in-house repository of RNAseq data sets with publicly available studies, this project will further explore the cellular heterogeneity of prostate tumours and the plasticity of cancer cells in …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Measuring higher education performance: a global comparisons using network data envelopment analysis
The research objective focuses on comparing the top 100 universities (according to the Times Higher Education) from 2010 to 2020. The objective of the project is fourfold. First, to derive appropriate research outputs per university. Second, employ a Network DEA approach to identify (in)efficiencies within the network. Third, to measure productivity change of universities using the Fare-Primont index. Fourth, to determine sources of (in)efficiencies and productivity.This project is both theoretical and applied. The applicant should possess strong mathematical and computational …
- Study level
- PhD
- Faculty
- Faculty of Business and Law
- School
- School of Economics and Finance
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