Driving the Clean Energy Transition with Artificial Intelligence

Overview

The clean energy transition requires not only technological advances but also changes in how individuals and organisations understand, adopt, and use energy technologies. While AI is widely applied to energy forecasting, optimisation, and control, many solutions overlook behavioural, social, and equity dimensions of energy use. As a result, technically sophisticated systems may fail to achieve meaningful real-world impact. There is a need for research that integrates AI with behavioural and information systems perspectives to develop human-centred, explainable, and decision-support oriented energy solutions.

Start date

2 November, 2026

End date

19 February, 2027

Location

QUT Gardens Point Campus

Additional information

The scope of the project will be discussed and refined in consultation with the student, taking into account their prior experience, skills, and research interests. Students will receive guidance throughout the project, including support with relevant literature, research design, data analysis, and the development of a clear and feasible project plan. This topic would suit students who are interested in applying information systems research to real-world sustainability, energy, or behavioural challenges and who are keen to develop their analytical and research skills.

Keywords

• Artificial Intelligence
• Clean Energy
• Information Systems
• Sustainability
• Machine Learning
• Energy Analytics

Contact

Dr Kenan Degirmenci

+61 7 3138 4181

kenan.degirmenci@qut.edu.au