Fang Duan

Fang Duan is a Lecturer in the Department of Electronic & Electrical Engineering IAAPS at the University of Bath. He holds visiting researcher positions at the University of Huddersfield (since 2024) and the University of Central Florida (2018–2019). His research focuses on condition monitoring of electric motors, fault diagnosis/prognosis in rotational machines (e.g., helicopter gearboxes), asset management, and AI applications in power electronics. Duan has contributed to UN Sustainable Development Goals through his work in sustainable energy systems.

Education: He earned a Doctor of Engineering (2010–2014) from the University of Adelaide, specializing in induction motor fault diagnosis. He also holds a Master of Science (2009–2010) and Master of Engineering (2007–2008) in Electrical Engineering.

Research Projects: He leads/co-leads two major projects: 'AI-Power: Artificial Intelligence for Next Generation Power Electronics' (2021–2027) and 'Physics-Informed Data-Driven Methods for Condition Monitoring of Wind Turbine Generators' (2021–2023). These focus on AI-driven power systems, renewable energy infrastructure, and predictive maintenance.

Publications (2023–2024): His recent work includes advancements in wireless power transfer systems, structural control of wind turbines using MR dampers, and underwater corrosion monitoring via RFID. These articles reflect his interdisciplinary approach to energy systems, sensor technology, and smart control algorithms.

Collaborations: Active in global research networks, Duan’s work spans Australia, the UK, and the US, with a focus on sustainable technologies and critical infrastructure.