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 476 matching student topics
Displaying 73–84 of 476 results
The dark side of robotic process automation
Pandemics such as COVID 19 have forced organisations to pursue hyper-automation to maintain operational sustainability. Many organisations are keen to adopt Robotic Process Automation (RPA) to dramatically improve operational efficiency. However, evidence to date highlighted various associated challenges associated with adoption of RPA in organisations.Furthermore, recent surveys by consultant organisations found a high RPA project fail rate and their inability to meet the expected return on investment.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Future Enterprise
Alleviating corruption: a data driven perspective
Corruption is cited as among the greatest challenges faced by government and citizenry the world over and threatens to undermine the very trust that is essential for a functioning democratic society. In order to earn and maintain public trust, governments at all levels must continuously strive to reduce corruption and uphold the highest levels of integrity.Amidst the countless human interactions and electronic transactions that occur within the public service on a daily basis are a complex and ever-changing variety of …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Understanding responsible deployment of computer vision for urban planning
Advances in artificial intelligence (AI) offer urban planning practice many novel prospects. By the responsive use of AI, planners can effectively analyse data, improve processes, increase efficiency, and prioritise human-centric aspects of planning to develop sustainable cities. Computer vision is one of the key areas where responsible AI is applied in urban planning to revolutionise the analysis and interpretation of visual data, like images and videos captured in cities to aid decision and plan making processes. While the potential impacts …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Parameter identifiability for stochastic processes in biological systems
Stochastic models are used in biology to account for inherent randomness in many cellular processes, for example gene regulatory networks. Noise is often thought to obscure information, however, there is an increasing understanding that some randomness contains vitally important information about underlying biological processes.When applying these models to interpret and learn from data, unknown parameters in the model need to be estimated. However, not all data will contribute to a given estimation task regardless of the data quantity and quality. …
- Study level
- PhD, 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
Southern ocean aerosols: Sources, sinks and impact on cloud formation and climate
Robust prediction of human-induced global warming and future climate requires more accurate climate models. Currently, aerosol-clouds interactions represent the largest source of uncertainty in our global climate models. To reduce this uncertainty, we need a better understanding of aerosol sources, chemical and physical properties, and processes impacting their growth to sizes where they can act as Cloud Condensation Nuclei (CCN) and interact with incoming solar radiation.The Southern Ocean is a region of the world where climate and weather models, including …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
- Research centre(s)
-
Centre for the Environment
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
Unlocking the Potential of Simplex-Truncated Distributions
This PhD project aims to develop new methods for generating random samples from a specific type of probability distributions called simplex-truncated distributions. These distributions are commonly used in various fields such as statistics, machine learning, and biology.The project will involve the development of new techniques to generate random samples from simplex-truncated distributions. These techniques are based on a method called continuous-time Monte Carlo which is a cutting edge method in statistics that can generate random samples from complex distributions.The main …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Understanding and designing for digital self-care
The aim of this project is to better understand self-care practices with digital technologies amongst young adults and to explore opportunities for digital technology design.Self-care is a process of purposeful engagement in practices that promote holistic health and well-being of the self. Holistic health implies overall health and this encompasses more than just physical health but also includes mental, emotional and even spiritual health of a person. For some people, cooking can be a form of self-care to eat healthily …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Low-cost portable Magnetic Resonance Imaging for clinical applications
The aim of this project is to develop accurate low-cost medical imaging methodology for pseudo-3D mapping of Mammographic Density (MD) within the breast. MD is the degree of radio-opacity (“whiteness”) in an X-ray mammogram. It has implications for breast cancer risk, ease of detection of breast cancer, and monitoring of the efficacy of hormonal breast cancer prevention or anti-cancer treatments.Healthcare ChallengeThere is a growing need for affordable and accurate quantitative assessment of MD without ionising radiation. Magnetic resonance imaging (MRI) …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
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