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 465 matching student topics
Displaying 97–108 of 465 results
Develop microfluidic technologies for cardiovascular and cerebrovascular diseases
The sudden rupture of vulnerable atherosclerotic plaques and subsequent thrombosis formations are responsible for most acute vascular syndromes, such as myocardial infarction and stroke. Many victims who are apparently healthy die suddenly with no prior symptoms. Such deaths could be prevented through surgery or alternative medical therapy, if vulnerable plaques were identified earlier in their natural progression.To address this pressing need, we're developing simple-to-use, high-throughput and highly-informative microfluidic biochips to understand the sequences of molecular events underlying biomechanical thrombosis (mechanobiology). …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Development of a Microfluidic Gut-Brain Axis Chip
The gut microbiome refers to the collection of micro-organisms that are living symbiotically in the human or animal gastrointestinal tract (defined as the “microbiota”), their genetic material as well as the surrounding environmental habitat. It is now appreciated that the microbiome plays an important role in human health and diseases. Many neurodegenerative diseases, such as Parkinson's Disease have been linked to dysregulation of the gut microbiota. However, it is difficult to study gut-brain axis using animal models due to inter-species …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Centre for Microbiome Research
Big Data ideas for GLMs
The goal of this project is to develop new Bayesian methods for large-scale data analysis using subsampling techniques. The focus of the project will be on generalised linear models (GLMs), which are commonly used models in statistics and machine learning.One of the main challenges in using Bayesian statistics with big data is the high computational cost associated with processing big datasets. The proposed project aims to address this challenge by developing new subsampling techniques for Piecewise Deterministic Markov Process (PDMP) …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Continuous time samplers (MCMC at the limit!)
The goal of this project is to develop new continuous time Monte Carlo methods for efficient sampling from high-dimensional distributions. Continuous-time Monte Carlo methods are a class of algorithms that use continuous-time dynamics to generate samples from target distributions, rather than the discrete-time dynamics used in traditional Markov chain Monte Carlo (MCMC) methods. These methods have been shown to have faster mixing and better exploration of the state space, making them particularly appealing samplers for challenging distributions.The main objectives of …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Analysis of professional squash matches
This project concerns computer vision and statistical analysis of performance in professional level matches in the game of squash.The goal is to use computer vision and existing systems to capture and analyse patterns of play, allowing coaches and professional players to develop strategies to improve performance, to counter particular types of play and even to tailor game plans to attack individual opponents.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data 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
Unified def-site and use-site security policies for component-based software systems
Securing the information manipulated by computer systems, such as privacy and integrity in social software, is a challenge. Traditional methods to impose limits on the information disclosure, such as access control lists, firewalls, and cryptography, provide no guarantees about information propagation. For instance, cryptography provides no guarantees about the confidentiality of the data are given once it is decrypted.Information flow control (IFC) is the problem of ensuring secure information flow according to specified policies within computer systems. Modern applications are …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
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
Systematic evaluation towards the analysis of open-source supply chain on ML4SE tasks
Applying machine learning algorithms to source code related SE task is rapidly developing and attracts the attention from both researchers and industry engineers. While there are many program languages available, applying such techniques, i.e., the representation learning models, for different languages may achieve different performance. Particularly, they all have their own strict syntax, which determines the abstract syntax tree. Thus, a lot of different open-source supply chain are available, for example the parsing tools are used to build AST from …
- 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
Identifying disease distress in patients with chronic venous leg ulcers
Venous leg ulcers (VLUs) make up 70% of all chronic leg ulcers. Unfortunately, around 30% of VLUs fail to heal in a 24-week period often despite evidence-based practice. Chronic VLUs impose a significant burden on people with these ulcers. Disease related distress has been explored in diabetes and inflammatory bowel disease but has not been explored in chronic wounds.Research has completed phase one of this study (secondary analysis of existing data), phase two (focus group to explore the findings), phase …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Nursing
Foreign direct investment for inclusive growth
Multinational enterprises (MNEs) attract a lot of bad press worldwide, sometimes with good cause: think of MNEs not paying their taxes, or possible threats to national security. Easily overlooked, however, are the extensive benefits that foreign direct investment (FDI) can bring to a host economy. This includes ‘spillovers’ from foreign firms and domestic multinational eneterprises that boost the productivity and innovation of local firms. This research project explores the mechanisms by which FDI impacts the productivity and innovation in domestic …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Business and Law
- School
- School of Advertising, Marketing and Public Relations
- Research centre(s)
-
Australian Centre for Entrepreneurship Research
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