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 84 matching student topics
Displaying 1–12 of 84 results
Mathematical modelling of cell-to-cell communication via extracellular vesicles (EVs)
Extracellular vesicles (EVs) are membrane bound packages of information constantly being released by all living cells, including bacteria. There are many types and sizes of EVs. Each EV type contains its own distinctive cargo consisting of characteristic DNA, RNA, and proteins. We are just beginning to understand the many roles of EVs to maintain the health of the cell producing the EVs, and to communicate with other cell types that take up the EVs produced by neighbouring cells. Since EVs …
- Study level
- Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
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, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Optimising delivery of a novel nose-to-brain treatment for brain cancer
Glioblastoma multiforme (GBM) is an aggressive brain cancer with no curative treatment and poor prognosis. One of the biggest challenges with treating GBM is the inability of treatment to cross the blood-brain barrier resulting in poor drug distribution in the brain. Fortunately, scientists have recently developed a novel nose-to-brain delivery system that uses nanoparticles loaded with a chemotherapy drug called paclitaxel. Initial treatment investigations in vivo are showing significant promise in reducing and controlling the tumour burden. While exciting, before …
- Study level
- Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Participatory Visualisation of Smart City Data
This PhD project will be affiliated with FrontierSI and Value Australia and contribute to its goals and objectives around smart cities, digital twins, and automated land valuations. Although consumers contribute much of the data upon which these smart city technologies operate, its systems often remain opaque black boxes closed off to public understanding, scrutiny and control. There are also serious concerns around privacy and loss of autonomy.This PhD project addresses these issues by exploring new methods for the participatory visualisation …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
-
Design Lab
Overcoming the challenges of sensitive data via synthetic data generation (case study)
In the 21st Century, there is an abundance of data, often containing insights that could benefit a number of stakeholders. However, despite this opportunity, it is often the case that the data is sensitive and can not be released by organisations or government agencies due to privacy concerns. One possible solution to the above dilemma is to instead carefully construct a 'twin' data set that contains similar information (and ideally, the same insights) as the original data set, but without …
- Study level
- Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Data-driven and process-aware workforce analytics
Modern information systems in today’s organisations record massive amount of event log data capturing the execution of day-to-day core processes within and across organisations. Mining these event log data to drive process analytics and knowledge discovery is known as process mining. To date various process mining techniques have been developed to help extract insights about the actual processes with the ultimate goal to organisations' workforce capability and capacity building.As an important sub-field of process mining, organisational mining focuses on discovering …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Explainable AI-enabled predictive analytics
Modern predictive analytics underpinned by AI-enabled learning (such as machine learning, deep learning) techniques has become a key enabler to the automation of data-driven decision making. In the context of process monitoring and forecast, predictive analytics has been applied to making predictions about the future state of a running process instance - for example, which task will be carried out next, when and who will perform the task, when will an ongoing process instance complete, what will be the outcome …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Transport big data analytics: Imputing missing data
The missing data problem is often unavoidable for real-world data collection systems because of a variety of factors, such as sensor malfunctioning, maintenance work, transmission errors, and so on. Filling in missing information in a dataset is an important requirement for many machine-learning algorithms that require a complete dataset as input. Data imputation algorithms aim at filling the missing information in a dataset. Many missing data imputation techniques exist in the literature, with applications demonstrated on various types of datasets. …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Indoor sensors to measure and visualise environmental data
We have an ongoing project that investigates how people change their work environment to suit their comfort needs. We have existing electronic devices that we want to optimise for better correlation and visualisation of the indoor climate measurements (lighting, thermal, air quality, occupancy). This would contribute to devices that are better integrated and more responsive to the demands of occupants.
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Information Systems
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, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Information Systems
Efficient parameter estimation for agent-based models of tumour growth
Cancer is an extremely heterogeneous disease, particularly at the cellular level. Cells within a single cancerous tumour undergo vastly different rates of proliferation based on their location and specific genetic mutations. Capturing this stochasticity in cell behaviour and its effect on tumour growth is challenging with a deterministic system, e.g. ordinary differential equations, however, is possible with an agent-based model (ABM). In an ABM, cells are modelled as individual agents that have a probability of proliferation and movement in each …
- Study level
- Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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