The AI for Quantum and Energy Systems (AI4QES) Lab focuses on developing AI foundations and applications to address complex scientific and engineering challenges in quantum technologies and energy systems.
Lab Director
Professor Daoyi Dong, Lab Director
Based at the Australian Artificial Intelligence Institute, the Lab brings together research in machine learning, reinforcement learning, quantum control, quantum machine learning, battery intelligence, smart grids and energy sustainability. The Lab aims to advance next-generation AI methods that can support the discovery, modelling, optimisation and control of complex quantum and energy systems. Our research connects fundamental AI innovation with high-impact application areas, including quantum technologies, batteries, electric vehicles, renewable energy integration, power grids and sustainable energy systems.
The Lab’s research focuses on five interconnected areas:
- quantum machine learning;
- AI for quantum technologies;
- AI for batteries and energy storage;
- AI for smart grids and power systems;
- AI for energy sustainability.
Across these areas, AI4QES develops data-driven, learning-based and optimisation-oriented approaches for modelling complex systems, improving system performance, supporting decision-making and enabling intelligent automation.
Collaboration and impact
AI4QES works collaboratively with researchers across UTS, industry partners, government organisations and international collaborators. The Lab supports joint grant applications, high-quality publications, HDR supervision, research training and academic events. The Lab welcomes collaboration with colleagues and partners interested in AI-enabled quantum technologies, battery systems, electric mobility, renewable energy integration, smart grids and energy sustainability.
