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.

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Found 661 matching student topics

Displaying 85–96 of 661 results

Citizen-developers: challenges and opportunities for low-code/no-code automation

Robotic Process Automation (RPA) is becoming a popular choice for organisations to support their digital transformation and to maintain operational resilience. Many organisations are keen to adopt Robotic Process Automation (RPA) to dramatically improve operational efficiency. Many organisations train and assign their staff as “citizen-developer” to design, test, and maintain the bots using Low-Code/No-Code platforms. However, there are number of issues surfaced when using organisational employees as citizen developer ranging from technical & process capabilities to scalability of RPA.

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

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

UAV navigation in GPS denied environments

This PhD project aims to develop a framework for unmanned aerial vehicles (UAV), which optimally balances localisation, mapping and other objectives in order to solve sequential decision tasks under map and pose uncertainty. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining simultaneous localisation and mapping algorithms with partially observable markov decision processes. The project’s expected outcomes will enable UAVs to solve multiple objectives under map and pose uncertainty in GPS-denied environments. This …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Automating drone traffic management systems

Unmanned Traffic Management (UTM) describes a set of systems, services and procedures that will be developed to manage drone (unmanned aircraft systems/unmanned aerial vehicle/remotely piloted aircraft) operations in and around our cities. From surveillance tasks and package delivery through to passenger transport, UTM will be essentially in ensuring safe and efficient use of our airspace. Essentially, UTM is a new air traffic control system for drones with high levels of automation and advanced decision making and control. This research aims …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Understanding the impacts of biodiversity-focused interventions to agri-food systems on people and nature

Despite efforts to monitor and manage declining species and ecosystems around the world, biodiversity is still not routinely included in mainstream decision-making and continues to decline at the highest rate in human history. Added to this is the problem that both natural and agri-food systems are continually changing due to human and natural disturbances, with climate change likely to increase the impacts of extreme events like drought, fire and economic shocks. Because of large uncertainties and trade-offs between many human …

Study level
PhD
Faculty
Faculty of Science
School
School of Biology and Environmental Science
Research centre(s)
Centre for Agriculture and the Bioeconomy
Centre for the Environment

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

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

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

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