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 11 matching student topics
Displaying 1–11 of 11 results
Augmented reality interfaces for autonomous vehicles
We're seeking brilliant and highly motivated students to work on an project seeking to improve the accessibility and usability of automated vehicles for disadvantaged users.Automated Vehicles are often touted as a solution to enable mobility for older users and people with disabilities, but these user groups are rarely included in their design. As a result, current developments are largely focused on the needs and skills of affluent, younger users, and ironically risk to further marginalise, instead of empowering, those who …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Internet of Mobile Energy
The emergence of the two-way communication model and Distributed Energy Sources (DES) is transforming traditional power systems from largely centralised energy production to more decentralised and connected management systems. This is called the 'smart grid'.As the smart grid evolves, electric vehicles (EVs) are emerging as unconventional and highly-disruptive participants in the grid that can add significant benefit and flexibility. Notably, EVs are equipped with a relatively high capacity battery that stores energy to power the vehicle.EV batteries, coupled with the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Understanding energy demand behaviours in Internet of Vehicles (IoV) systems
The internet of vehicles (IoV) plays an important role in the internet of things (IoT) value system. IoV enables vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications through enhanced connectivity and data-driven decision-making. However, given the importance of energy infrastructures in IoV systems (Shen et al., 2021), the role of energy demand behaviours is yet overlooked.In the context of electric vehicles as low-emission consumer energy resources (Degirmenci & Breitner, 2017), V2V and V2I networks improve the communication with other vehicles and charging …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Uberizing charging station allocations for electric vehicles
Uberization refers to the use of digital services to offer direct contact between service providers and service seekers (Bootz et al., 2022), which provides new opportunities for peer-to-peer charging of electric vehicles (Hu et al., 2021).In this project, we explore the uberization of peer-to-peer charging from a sharing economy perspective and analyse opportunities for service innovation of electric vehicles.ReferencesBootz, J.-P., Michel, S., Pallud, J., & Monti, R. (2022). Possible changes of Industry 4.0 in 2030 in the face of uberization: …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Challenges to data sharing of electric vehicles: alleviating privacy concerns with edge computing
The Australian Government has released Australia’s first National Electric Vehicle Strategy to increase the uptake of electric vehicles (EVs) in Australia (Australian Government, 2023), which has the potential to reduce carbon emissions substantially, given that electricity is produced from renewable energy sources (Degirmenci & Breitner, 2017).Despite environmental benefits like reduced carbon emissions, EV owners become increasingly concerned about their privacy due to enhanced EV connectivity and increased personal data sharing through EV digital services. Edge computing, where data is processed …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Facilitating Towards Sustainable Electric Vehicles Trading System
The number of Electric Vehicles (EVs) on the road is expected to reach 145 million by 2030. As the number of EVs on the road increases, the demand for energy to charge these vehicles also grows. Traditional charging infrastructure may not meet the increasing energy demands, which may lead to increased waiting time in those charging stations. The EV-EV trading scheme is a promising solution that allows EV owners to access additional energy from nearby EVs. This scheme has attracted …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
A Human-centric eXplainable Automated Vehicle
CARRS-Q has developed a strong expertise in AV and ADAS, and operate an Automated Vehicle for its research on test track and open roads.We have collected more than 12,000km of sensor data in various Australian conditions, and we are progressing quickly to a broader understanding of safe operation of AV technologies on our roads. We are looking for PhD candidates to progress further on these topics. PhD positions are available for highly motivated domestic and/or international students to work on …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Psychology and Counselling
Human-machine interface (HMI) design to manage driver engagement in automated vehicles
We are seeking an enthusiastic and dedicated individual to join the Empathic Machines project as an HCI/HMI PhD Researcher. This interdisciplinary research project, conducted in collaboration with Queensland University of Technology (QUT) and Seeing Machines, aims to explore the concept of empathic machines in the context of driver monitoring systems (DMS) and automated driving. The successful candidate will contribute to advancing the understanding of human-machine interaction, interface design, and attention sharing to enhance safety and user experience in automated vehicles.A …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Psychology and Counselling
- Research centre(s)
-
Centre for Future Mobility
Identifying novel pheno-endotypes in children with chronic cough
Chronic wet cough is among the commonest symptoms of chronic lung disease. In Australia, the most common cause of childhood chronic wet cough is protracted bacterial bronchitis (PBB), a clinical entity we first described. It has now been shown to be a precursor to bronchiectasis, which causes substantial morbidity and mortality, especially from acute respiratory exacerbations. Lung inflammation in children with persistent chronic wet cough is an important driver of ongoing and progressive tissue damage, leading to bronchiectasis, highlighting the …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Public Health and Social Work
- Research centre(s)
- Centre for Healthcare Transformation
Australian Centre for Health Services Innovation
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
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Model predictive control of connected vehicle platoons
Control of connected vehicle platoons can ensure the swift movement of traffic through a city by sharing vehicles' states and desired actuation. This networked control design can alleviate traffic jams, reduce vehicle emissions, and reduce fuel usage through improved aerodynamics. Model Predictive Control algorithms are a natural solution to address constraints arising from both communications and system dynamics. A key challenge is to design distributed control algorithms that are robust to disturbances in the environment and to stochastic information from …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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.