Associate Professor Huadong Mo is at the School of Systems and Computing, UNSW Canberra, University of New South Wales, Australia. He serves as the Inaugural Director of the Resilient Intelligent Systems for Clean Energy Research (RISER) Hub and Postgraduate Systems Engineering Coordinator. Mo earned a B.E. degree in automation from the University of Science and Technology of China in 2012 and a Ph.D. in systems engineering and engineering management from the City University of Hong Kong in 2016. During his Ph.D., he was a visiting research student at Centrale Supelec in France, Tsinghua University in China, and the University of Science and Technology Beijing. From 2016 to 2019, he worked as a Research Associate at the Reliability and Risk Engineering Lab, Institute of Energy Technology, ETH Zurich, Switzerland. He joined UNSW Canberra as a Lecturer in the School of Engineering and Information Technology in 2019, advanced to Senior Lecturer in the School of Systems and Computing in 2021, and was promoted to Associate Professor in 2025.

Mo's research focuses on enhancing the resilience, performance, and security of complex systems through learning-based algorithms, particularly in renewable energy systems, cyber-physical systems, and manufacturing systems. His interests include advanced sensing and data analysis for prognostics and health management, sustainable transportation and energy systems, robust operation of power and energy systems under extreme events, and quantum-inspired reinforcement learning-based lifelong asset management. He has co-authored the book Cyber-Physical Distributed Systems Modeling, Reliability Analysis and Applications (John Wiley & Sons, 2021). Recent key publications include 'Rule-based peak shaving strategy with battery storage: Evaluating socio-economic impacts in regional grids' (Energy and Buildings, 2026), 'Peak Load Mitigation Using Battery Energy Storage Systems for a Regional Distribution Network' (IEEE Transactions on Industry Applications, 2026), and 'TFTformer: A novel transformer based model for short-term load forecasting' (International Journal of Electrical Power and Energy Systems, 2025). Mo has received the IEEE SMC Early Career Award 2024, Visiting Research Fellowship (Pre-award of Jean d'Alembert Pour Fellowship) in 2023, ARC PGC Supervisor Award 2021, and multiple best paper and presentation awards, including at IEEE ICEBE 2024 and ICEMS 2021. His contributions extend to supervisory excellence, evidenced by a Gold Medal in the 2024 China International College Student Innovation Competition as supervisor, and IEEE SMC Outstanding Chapter Award 2021 as co-Chair.

Professional Email: huadong.mo@unsw.edu.au