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 207 matching student topics
Displaying 157–168 of 207 results
Optimising bone shape with memory networks
Bone is a dynamic tissue that optimises its shape to the mechanical loads that it carries. Bone mass is accrued where loads are high, and reduced where loads are low. This adaptation of bone tissue to mechanical loads is well-known and observed in many instances. However, what serves as a reference mechanical state in this shape optimisation remains largely unknown.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Praeclarus process-data quality framework
Praeclarus is an open-source software framework that aims to facilitate data pre-processing for process mining. Process mining is specialised data mining focusing on process-data. It is of high interest to industry, with the market doubling every two years (e.g., increasing from $550M in 2020 to $1B in 2022). This market increase has meant that big companies like Microsoft, SAP, and IBM are acquiring process mining vendors such is Minit, Signavio, and myInvenio.Recent process mining surveys show that more than 60% …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Uncovering the dark transcriptome and proteome with long-read sequencing
Parts of the transcriptome and proteome are invisible to current technologies. We refer to them as the dark transcriptome and proteome and they encompass uncharacterised mRNA and protein isoforms. Importantly, this hidden molecular phenotype is believed to play a critical role in animal health and behavior.Recent developments in mRNA analytical methods such as long-read sequencing (PacBio, ONT) have enabled better characterization of isoforms and are redefining the transcriptome landscape in many species. We and others have found that data generated …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Biology and Environmental Science
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
Ubiquitous visual positioning devices
Everything that moves is defined and limited by its ability to navigate the world in which it exists. Knowing where you are located in the world is a key navigational capability for people, animals, and both autonomous and human-operated platforms ranging from self-driving cars to aircraft.But accurate and trustworthy positional knowledge has widespread potential implications beyond navigation: it can, for example, allow life-and-death decisions in defence and in tracking the spread of global pandemics. Both the potential of and problems …
- Study level
- Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
Multi-UAV navigation in GPS denied environments
The aim of this research is to develop a framework for multiple Unmanned Aerial Vehicles (UAV), that balances information sharing, exploration, localization, mapping, and other planning objectives thus allowing a team of UAVs to navigate in complex environments in time critical situations. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining Simultaneous Localization and Mapping (SLAM) algorithms with Partially Observable Markov Decision Processes (POMDP) and Deep Reinforcement learning. This should provide significant benefits, …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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
Capturing the impact of patient variability in a novel cancer treatment
In 2015, the Food and Drug Association (FDA) approved a lab-engineered virus for the treatment of melanoma (skin cancer). Since then, there has been a significant increase in the number of lab-grown viruses that are being tested in clinical trials as potential treatments of cancer. Unfortunately, it seems that a large number of patients in these clinical trials fail under this treatment and currently there is no way to distinguish between responders and non-responders to treatment.Fortunately, we can use mathematics …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data 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
Habitable water infrastructures
This project explores buildings, public/civic spaces, and landscapes as water infrastructure. Water is integral to human survival; hence understanding buildings and urban spaces as habitable water infrastructure has the potential to mitigate the effects of the climate crisis and navigate too much water (floods) and too little water (drought) while offering different modes of occupation.With increasing rainfall intensities, floods, rising sea levels, and drought, the pervasive dichotomy between habitable spaces and water infrastructures can no longer hold. The two can't …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Gamified process-data cleaning
Despite the importance of data quality, it is often compromised. The majority of the time and energy in most data science projects is spent on data cleaning. Process-oriented data mining (process mining) is not an exception. A recent process mining survey shows that more than 60% of the time and effort is spent on data transformation and pre-processing. While, in most cases, the engagement of domain experts is required for accurate data cleaning, it is challenging to engage them in …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
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