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 508 matching student topics
Displaying 325–336 of 508 results
Prescriptive process analytics
With growing significance of data there is a need to harness the potential of that data for improved business operations. Historical data is often to provide a descriptive overview of how business processes have performed in the past. However, there is a need to be proactive and take appropriate actions to ensure that business processes perform in an optimal manner. Prescriptive analytics is a process that analyzes data and provides instant recommendations on how to optimize business practices. Prescriptive analytics …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Human biomarkers of stress, trauma, and memories of fear
Understanding how disorders such as posttraumatic stress disorder develop following trauma is a contemporary challenge for researchers in psychology. The best explanations involve a combination of psychological and biological factors that interact during and following trauma to create a range of troubling symptoms. This project will use cutting edge technology at QUT to provide insights into how a mix of biology and behaviour can result in exacerbated stress responses and threat memories in experimental and real-world settings.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Psychology and Counselling
Microfluidic chip-based tumor-immune cancer models for biomarker discovery
In-vitro profiling of tumour-immune cell interactions in proximity can provide valuable insight into patient response to new combinatorial immunotherapies that are in the pipeline and currently being tested in clinical trials. These in-vitro models allow for a more controlled and isolated environment and provide a methodical approach for generating quantifiable data characterizing the interactions between target and effector cells. Traditionally executed in well-plates, tumour-immune models have been slowly moving towards a microfluidic chip-based approach for several reasons: better control over …
- 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
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
The effects of trust on government operations
For a government to operate efficiently, the trust of its constituents, as well as the global community, is considered to be of substantial importance. A lack of trust could impair the government’s ability to effectively manage and fund its operations from collecting taxes and external investment. However, further research is required to understand the underlying trust mechanisms and their influence on governments’ performance. To address this research gap, the project will examine how trust in government is determined, evaluate how …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Business and Law
- School
- School of Accountancy
- Research centre(s)
- Centre for Future Enterprise
Identifying Indigenous contributions to knowledge
The Australian Census collects data every ten years to reflect who we are as a nation. But the data collected by the Census only tells part of our story.Indigenous people lived in Australia for thousands of years before the arrival of European settlers, accumulating a wealth of knowledge about Australia's land, climate, flora and fauna. Researchers have only begun tapping this knowledge as the basis for modern scientific research.This project will combine machine learning and text-analytics tools to develop a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- 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
Visualisation and sonification for genomic data sets
Successive revolutions in sequencing technology over the past two decades have led to an explosion in the availability of genomic data. Analysing biological datasets and identifying relationships within them is challenging - some of the process can be automated but interactive exploration offers a number of advantages, and supports serendipitous discovery.This project looks at visual analytics and sonification - the use of sound and musical encodings - to enhance our understanding of biological networks.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
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