Student topics

The share of renewable energy in electricity generation has globally increased to 28.3%, however, an acceleration of the sustainable energy transition is required to limit worldwide temperature rise (REN21, 2022).Energy storage offers various benefits, such as balancing the mismatch between electricity supply and demand; however, due to its charge/discharge inefficiencies (energy storage results in a loss of at least 10% of electricity in the charge/discharge process), digital solutions are needed to manage grid equilibrium effectively (Watson et al., 2022).In this …

Study level

PhD, Master of Philosophy, Honours

School

School of Information Systems

Research centre(s)

Centre for Data Science

Consumers generally express positive attitudes towards renewable energies, recognizing system values such as environmental benefits and sustainability advantages (Zhang et al., 2024). However, the actual adoption and use of renewable energy services may not align with their expressed preferences.This paradox stems from various customer value-related barriers, such as high upfront costs, limited awareness, and concerns about reliability or convenience, which hinder widespread consumer adoption of renewable energy solutions (Jridi et al., 2016).In this project, we analyse the consumer adoption paradox …

Study level

PhD, Master of Philosophy, Honours

School

School of Information Systems

Research centre(s)

Centre for Behavioural Economics, Society and Technology

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

School

School of Information Systems

Research centre(s)

Centre for Data Science

Artificial intelligence (AI) can play a significant role in analyzing and predicting energy consumption and production patterns from renewable sources such as solar and wind (Lyu & Liu 2021). This is particularly important due to the key challenge of intermittency, where major renewable sources for electricity, such as solar and wind, are subject to the inconsistencies of the weather (Watson et al., 2022).In this project, we investigate how AI and machine learning algorithms can optimize smart grids and other components …

Study level

PhD, Master of Philosophy, Honours

School

School of Information Systems

Research centre(s)

Centre for Data Science

The increasing frequency and intensity of extreme weather events, such as intense heatwaves, floods, and bushfires, is triggering disruptive disasters that have a significant impact on communities, ecosystems, and economies. While our national climate change adaptation strategy places a paramount focus on enhancing community resilience, it is crucial to recognise that not all communities face climate risks in the same manner. Diverse communities exhibit varying capacities to respond and adapt to distinct climate hazards. This reality underscores the imperative for …

Study level

Honours

School

School of Architecture and Built Environment

Research centre(s)

Centre for the Environment

Renewable electricity is remarkably cheap, and is only going to get cheaper. However, existing state-of-the-art CO2 capture and conversion processes use thermal energy (typically generated by burning natural gas). This modelling project will investigate electrochemical techniques for capturing CO2 from air (direct air capture) and converting it to useful chemicals and materials.

Study level

PhD

School

School of Mechanical, Medical and Process Engineering

The Australian Commission on Safety and Quality in Health Care 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 ability to …

Study level

PhD, Master of Philosophy, Honours

School

School of Computer Science

Research centre(s)

Centre for Data Science

In process mining, sequence analysis algorithms are used to discover computational models of process data, and to analyse them. The insights from these models and analysis then improve the processes in organisations in many real-life domains - from manufacturing, to government, to healthcare. Haskell is a powerful functional programming language well suited to problems involving formal reasoning and pattern matching. This project would advance process mining research by building high-quality, high performance libraries in Haskell for fundamental process mining activities …

Study level

Honours

School

School of Information Systems

Software vulnerabilities have been considered as significant reliability threats to the general public, especially critical infrastructures. Many approaches have been proposed to detect vulnerabilities in source code to avoid any damages they pose when exploited. Conventional approaches include static analysis and dynamic analysis. Static analysis uses pre-defined patterns or vulnerability dataset to scan and examine software source code to identify potential vulnerable code snippets. These patterns are manually crafted or identified by software developers or security experts, which are time-consuming. …

Study level

PhD, Master of Philosophy, Honours

School

School of Computer Science

Research centre(s)

Centre for Data Science

Quantum machine learning is the integration of quantum algorithms within machine learning programs with great potential to solve complex problems. For instance, Google’s Sycamore processor (61) performs in 200 seconds a task that would require 10,000 years using a classical computer.

Study level

PhD

School

School of Electrical Engineering and Robotics

I am looking for highly motivated and talented PhD students to work with us on robot localisation and navigation. The students would join my DECRA Fellowship project "Adaptive and Efficient Robot Positioning Through Model and Task Fusion" funded by the Australian Research Council, which provides substantial top-up scholarships in addition to QUT's tax-free base stipend.Robot positioningWhere are you? This is a fundamental question to which most of us usually know the answer. And so do the birds singing in our …

Study level

PhD

School

School of Electrical Engineering and Robotics

Research centre(s)

Centre for Robotics

As part of an ARC Future Fellowship project awarded to Luis Pedro Coelho, we aim to study small proteins with the aim of better understanding them and laying the groundwork for exploiting them for biotechnological purposes. Small proteins (up to 100 amino acids, but often much shorter) have vital roles in all areas of life, but have been neglected in research due to lack of methods.Particular projects in this topic include developing methods for determining function based on genomic context, …

Study level

PhD, Master of Philosophy, Honours

School

School of Biomedical Sciences

Research centre(s)

Centre for Microbiome Research