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 121–132 of 476 results
Addressing security challenges for the industrial internet of things
With the emergence of the Internet of Things (IoT) and Industry 4.0, there is a trend for applying these services and applications to a large-scale industrial area. The IoT paradigm has changed the way of interactions with the things that surround us. In essence, the IoT promises ubiquitous connection to the Internet, turning common objects into connected devices. It is predicted that there will be 50 billion connected devices at the end of the year 2022.Over the last few years, …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Optimal ecosystem management in rapidly changing systems
Delays in acting in collapsing ecosystems can be catastrophic. With every passing year, the chances that the ecosystem has progressed past some point of no return increases. Yet the research and development needed to develop a new technology can take a long time. Balance between these two dynamic processes is needed to determine the optimal length and effort for developing new technologies. This project will develop a method for finding the optimal schedule for developing technological readiness, social acceptability, a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Hierarchical visualisation of large social networks
Networks have been extensively used to capture social interactions, by representing individuals as nodes and their relationships as edges.Such networks have been used to model the spread of epidemics. A few nodes are 'infected', and over time they gradually infect their neighbours on the network, who in turn infect their neighbours, etc. This type of model can then be used to simulate different intervention strategies aimed at containing outbreaks.However, an important limitation is the difficulty to visualise these networks when …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Conservation is a noisy business: modelling the effects of stochasticity on wildlife management decisions
To conserve species in disturbed natural environments, we need to use mathematical models to predict the consequences of different interventions. Unfortunately, these models are based on partial information of complex systems, and the systems themselves are subject to substantial observational and process noise.We often use ordinary differential equations to describe ecosystems, like the classic logistic growth model:dn/dt = r n (1 - n / k)However, these models are deterministic, and they assume we know the values of the key parameters …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Bushfire design of residential buildings
This project aims to investigate the bushfire performance of residential buildings in the bushfire-prone areas of Australia. This includes a detailed review of:bushfire characteristicsradiant and convective heat ratestype of materials used to construct bushfire safe housesstructural and fire performance of external wall and roof panelsstructural and architectural building design requirementsThis comprehensive review will contribute towards developing conceptual models and design methods for external wall and roof systems for residential buildings in bushfire zones.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Materials Science
Changing the world with augmented creativity
We're seeking brilliant and highly motivated students to work on an Australian Research Council-funded project.Our goal is to transform augmented reality (AR) from a hyper-specialised tool for power users, into an enabler of creativity, socialisation, and new forms of community.We will reimagine augmented reality, from the current hyper-specialised tool for power users, into an enabler of creativity and imagination. We seek to engage with artists, designers, musicians, to explore new forms of creativity, art, and performance.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer 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
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
Predicting alternative states induced by multiple interacting feedbacks: seagrass ecosystems as a case study
This project seeks to explore the complex dynamics that might arise from multiple interacting feedbacks in marine ecosystems, by designing ordinary and/or partial differential equation models of these feedbacks and analysing the steady states and/or temporal dynamics of the proposed model(s).It has been hypothesised that many social and ecological systems exhibit alternative stable states due to feedback processes that keep the ecosystem in one state or the other. The result can be tipping points, which are difficult to predict but …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Tree-chain: a fast lightweight consensus algorithm for IoT applications
In recent years, blockchain adaptation in IoT has received tremendous attention due to its salient features including distributed management, security, anonymity, and auditability. However, conventional blockchains are significantly resource demanding and suffer from lack of throughput, delay in committing transactions, and low efficiency. We recently introduced a novel blockchain consensus algorithm known as Tree-chain, that bases the validator selection on an existing feature in all blockchains: hash function. Tree-chain achieves a fast throughput while ensuring the randomness and unpredictability of …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Computer Science
Hospital readmission prediction with domain knowledge
The Australian Commission on Safety and Quality in Health Care (the Commission) has highlighted that reducing avoidable hospital readmissions supports better health outcomes, improves patient safety and leads to greater efficiency in the health system. Previous studies have reported that up to 11% of the Emergency (ED) population are "heavy users" with a higher prevalence of psychosocial problems and often co-existing chronic medical conditions. All Australian governments have committed to reforms under the National Health Reform Agreement Addendum,1 and the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Semantic-based source code embeddings for software vulnerability discovery
Operational Technology (OT) is a field of computing which is becoming increasingly prominent in modern society. It is responsible for a variety of critical services, especially in industrial contexts, including power generation, manufacturing, transport, and many others. This important role makes OT an especially tempting target for malicious attackers. In order to counter this, tools must be developed to locate vulnerabilities and flaws in OT software systems before attacks can be launched. Vulnerability discovery in computer software systems including OT …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
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