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 26 matching student topics
Displaying 1–12 of 26 results
Development of high value products from mining waste resources
Mining represents one of the largest industry sectors in Australia. It is central to creating 1 million direct or indirect jobs and generates significant wealth to Australia. However, the mining industry produces a substantial amount of waste material which ideally needs to be recycled.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
Value-adding waste materials
Many industries generate copious amounts of waste products.Of particular interest are those wastes generated by the mining sector as typically a large fraction of the ore bodies are dumped or the agricultural sector.Potential solutions we are investigating include:converting aluminosilicate waste to zeolitestransforming inorganic waste to catalyst materialscreation of materials for water and wastewater treatmentmaking activated carbonrenewable fuels,
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
Green polymer-inorganic composite materials
Composite materials are widely researched and widely used in applications such as aircraft, automobiles, ships, structural components and even the space industry.There is a need to create new composite materials which are environmentally friendly and do not use fossil fuel based products. Moreover, the properties of the composites need to be improved while at the same time minimising the costs involved.Consequently our research group is working on composite materials which not only include inexpensive inorganic fillers from the mining sector …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
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
- Faculty
- Faculty of Science
- School
- School of Information Systems
- 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
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Multi-modal sentiment analysis
In deep learning models, language models and word embedding methods have become popular to understand the context of text data. Popular language models such as BERT have limitations in terms of the token length. There exist some corpora that have longer text with an average of 1000 tokens. Additionally, these corpora are text-heavy and only include some images.In our prior works, we have developed several multi-modality models on social media datasets.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Evaluation of language models and word embedding methods for natural language processing applications
In deep learning models, language models and word embedding methods have become popular to understand the context of text data. There exist many variants of these methods and have different limitations. This project will introduce you to the hot topic of language models and the fields of Natural Language Processing and Text Mining.
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
5G and IoT smart ontology learning
This project aims to investigate privacy preservation protocols in a 5G integrated IoT environment through an analysis of the depth of smart-device use in common smart domains. 5G’s addition to IoT-based smart devices will be effectively deployed and utilised by a large majority of individual and organisation-based users. The knowledge-based ontology and tools developed in the project will help form the new privacy preservation mechanisms that are required for the 5G enabled environment.The development of an ontology for 5G enabled …
- Study level
- PhD, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Data reasoning to extend domain knowledge in deep learning
A wide variety of companies now use personalized prediction models to improve customer satisfaction, for example, detecting cancer relapses, Detecting Attacks in Networks (e.g., SDN) or understanding Customer Online Shopping Behaviour. However, the dramatic increase in size and complexity of newly generated data from various sources is creating a number of challenges for domain experts to make personalized prediction.For example, early detection of cancer can drastically improve the chance and successful treatment. Recently, supervised deep learning has brought breakthroughs in …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
AI-Based Data Analysis on Multiple Imaging Modalities
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Examining approaches to mitigating customer aggression and abuse
The pace of change associated with modern businesses (Grewal et al., 2017; Grewal et al., 2020), and the introduction of new technologies has created heightened level of stress (technostress) and aggression (Chen et al., 2019). Adding to these stressors, COVID-19, which has forced businesses to adapt their processes and customer service interface (Ahmed et al., 2021; Jiang and Stylos, 2021; Roggeveen and Sethuraman, 2020). Research now finding that continued lockdowns, social distancing, and political rancour, all adding increased levels of …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Business and Law
- School
- School of Advertising, Marketing and Public Relations
Examining customer responses to body worn cameras
As a direct response to increasing customer aggression, retailers are implementing measures to keep frontline team members safe – assets such as body worn cameras (BWC) and duress watches. Concerningly, there is a dearth of research into these technologies in a retail setting, with much of the earlier research being undertaken in corrective services, policing and train guards.Current research identifies, in some cases, the presence of such technologies can lead to a ‘back-firing’ effect (the aggressive individual becomes more aggressive), …
- Study level
- PhD, Master of Philosophy
- School
- School of Advertising, Marketing and Public Relations
Contact us
If you have questions about the best options for you, the application process, your research topic, finding a supervisor or anything else, get in touch with us today.