Descrizione del progetto
Funding and duration
four year scholarship package totalling approximately $48,000 per annum tax exempt (2026 rate); four-year scholarship and research training program.
Project overview
Project title
Responsible AI for Smart Energy Adoption and Optimisation in Australian Households and Small Businesses
Project description
This Project will examine how AI-enabled digital tools can improve both the adoption and day-to-day use of distributed clean-energy systems, including rooftop solar, battery storage, and virtual power plant participation, for Australian households and small businesses. The Project will investigate why many users do not adopt these technologies, or do not use them efficiently after adoption, with a focus on behavioural, financial, and informational barriers. Using customer energy-use data, tariff information, weather forecasts, and distributed energy system performance data, the project will develop and evaluate machine-learning models to forecast electricity demand and solar generation, optimise battery charging and load shifting, and generate personalised recommendations for end users. The Project will also examine how responsible AI and user-centred digital design can improve trust, understanding, and decision quality.
Supervisory team
University
Name of university supervisor | Di Bu
Name of university | Macquarie University
Email address | di.bu@mq.edu.au
Faculty | Macquarie University FinTech and Banking Research Centre
CSIRO
Name of CSIRO supervisor | Dilum Bandara
Email address | dilum.bandara@csiro.au
CSIRO Research Unit | Technology
Industry
Name of industry supervisor | Dawei Huang
Name of organisation | Wattclub Pty Ltd
Email address | dawei@wattclub.com.au
Further details
Primary location of student | Macquarie University, Balaclava Road, Macquarie Park NSW 2113, Australia
Industry engagement component location | Wattclub Pty Ltd, Level 2, 6 Parkview Drive, Sydney Olympic Park NSW 2127, Australia
Other locations | CSIRO Marsfield, 26 Pembroke Road, Marsfield NSW 2122, Australia
Ideal student skillset | Essential skills: A strong background in a relevant discipline such as computer science, data science, information systems, software engineering, engineering, economics, behavioural finance, or another quantitative field. The student should be comfortable working with quantitative and unstructured data, conducting rigorous research, and translating technical findings into practical insights for industry. Strong programming skills in Python or similar tools, good written and verbal communication, and the ability to work across academic and industry environments will be important. An interest in interdisciplinary research at the intersection of AI, digital infrastructure, and the clean-energy transition is essential.Desirable skills: Experience in machine learning, data analytics, optimisation, statistics, software development, or digital platform research will be highly valued. Familiarity with energy systems, sustainability, consumer behaviour, or responsible AI is desirable.
Application close date | Open until position filled
Apply | MQ
CSIRO
New South Wales, Australia