ISEM Seminar Series
“Online Health Monitoring and Optimal Management of Renewable Assets”by Dr Huadong Mo Senior Lecturer University of New South Wales, Australia |
2 July 2025 (Wednesday), 4pm – 5pm Venue: E1-07-21/22 - ISEM Executive Classroom |
ABSTRACT
In this talk, I will present our recent advancements in health monitoring and optimal management of renewable energy assets, with a focus on lithium-ion batteries in electric vehicles and energy storage systems. I will introduce our advanced battery management system, which integrates state-of-the-art AI and IoT techniques for real-time battery health monitoring and anomaly detection. This system addresses key challenges, including data heterogeneity, AI explainability, scalability, data quality, and privacy concerns. Additionally, I will provide an overview of our recent contributions to enhancing the robustness of energy systems for net-zero emissions under extreme events, as well as the application of generative AI in industrial settings. |
Dr. Huadong Mo joined the University of New South Wales, Australia, as a Lecturer in 2019 and was promoted to Senior Lecturer in 2021. He received the 2024 IEEE SMC Early Career Award, becoming the fourth recipient since its inception in 2014. Additionally, he was awarded the 2023 Visiting Research Fellowship (Pre-award of the Jean d'Alembert Pour Fellowship) in France. Dr. Mo is currently the Coordinator of the Systems Engineering Discipline within the School of Systems and Computing. Previously, he was a Postdoctoral Fellow at the Swiss Federal Institute of Technology, Zurich. He earned a Bachelor's 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. Dr. Mo's research focuses on improving the reliability, resilience, performance, and security of complex systems using learning-based algorithms. His work primarily spans power and energy systems, cyber-physical systems, and manufacturing systems, leveraging advanced data collection and analysis techniques to uncover system evolution patterns under uncertainty. Over the years, he has published more than 80 SCI-indexed journal and conference papers, along with a monograph. Dr. Mo's research in Australia has secured approximately 5 million AUD in funding, primarily from the Australian Research Council (ARC) and other government-led initiatives, including Trailblazer, AEA, and the Energy Innovation Fund. |