Challenges and Opportunities for LVDC and MVDC in the Energy Transition
Prof. Johan Driesen, KU Leuven, Belgium

Abstract: The ongoing energy transition is increasingly enabled by advances in batteries, information and communication technologies, and power electronics. Power electronics in particular has emerged as a key enabler, acting as a game changer for electromobility, the large-scale integration of renewable energy sources, grid-connected battery storage, and the reliable operation of energy-intensive infrastructures such as data centres. As electrification scales up, conventional AC-based architectures face limitations in terms of efficiency, controllability, and flexibility. In this context, low-voltage and medium-voltage direct current (LVDC and MVDC) systems are gaining attention as promising alternatives to further support sustainable electrification. By reducing conversion stages and enabling more controllable power flows, DC systems offer opportunities for more flexible yet reliable operation, particularly at higher power levels. This seminar discusses the potential of LVDC and MVDC technologies, as well as the associated technical and operational challenges, drawing on research conducted at KU Leuven and the EnergyVille research centre in Belgium. Specific use cases, including high-power charging infrastructure for electric trucks and the powering of data centres, are presented to illustrate the opportunities and remaining hurdles for DC-based power systems in the energy transition.

Speaker's Bio: Johan Driesen received the MSc degree in 1996 as Electrical Engineer from the KU Leuven, Belgium. He received the PhD degree in Electrical Engineering at KU Leuven in 2000. In 2000-2001 he was a visiting researcher in the Imperial College of Science, Technology and Medicine, London, UK. In 2002 he was working at the University of California, Berkeley, USA. Currently, he is a full professor at the KU Leuven and teaches power electronics, renewables, drives and electromobility. He conducts research on distributed energy resources, including renewable energy systems, low-voltage DC-systems, power electronics and its applications, for instance in renewable energy, storage and electric vehicles. Within EnergyVille, the research collaboration specializing in energy in smart cities and buildings, in cooperation with VITO and Imec, Johan Driesen is involved in the programmes on power electronics, power systems and distributed energy sources. Currently he serves as the director of the KU Leuven Institute of Energy and Society. In 2026, he became an IEEE fellow for “contributions to the integration of renewables and electric vehicles in the electricity grid”.

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January 30, 2026, Friday, 4:30pm
ONLINE ONLY
Zoom ID 383 735 6917
Password 270831

From Roads to Skies: Learning to Coordinate Air–Ground Mobility for On-Demand Air Taxi Services
Mr Aoyu Pang, The Chinese University of Hong Kong, Shenzhen

Abstract: Urban Air Mobility (UAM) is emerging as a transformative solution to urban congestion, leveraging low-altitude airspace to complement traditional ground transportation. However, coordinating air taxis, vertiports, and ground vehicles remains challenging due to dynamic passenger demand, limited eVTOL capacity, and uneven vertiport utilization. In this talk, we present the Unified Air-Ground Mobility Coordination (UAGMC) framework, which integrates deep reinforcement learning (RL) with Vehicle-to-Everything (V2X) communication to optimize vertiport selection and air-ground routing in real time. Using UAGMC, passengers can experience efficient, door-to-door mobility as the system dynamically balances load across the network while minimizing travel time. We will showcase simulation results demonstrating significant reductions in travel time compared to conventional allocation strategies and discuss how our framework provides practical insights for future intelligent urban mobility solutions.

Speaker's Bio: Aoyu Pang is a Ph.D. student in Computer and Information Engineering at The Chinese University of Hong Kong, Shenzhen. He received his B.Eng. degree from Nanjing University of Aeronautics and Astronautics (NUAA) in 2023. His research focuses on intelligent transportation systems, urban air mobility, and reinforcement learning applications for smart cities. He has authored multiple papers in conferences and IEEE journals, including work published or under review at ICLR, NeurIPS, IEEE Transactions on Vehicular Technology (TVT), and IEEE Transactions on Intelligent Transportation Systems (TITS). He also serves as a reviewer for journals such as TITS.

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February 6, 2026, Friday, 4:30pm
Room FYW-3316
Zoom ID 859 8869 4437
Password 123456

Graph Learning for Network Robustness: Analysis and Optimization
Dr Yang Lou, Hiroshima University, Japan

Abstract: Maintaining and restoring network functionality under structural disturbances or malicious attacks represents a core challenge in network science and graph learning. This capability, known as network robustness, is critical for systems such as transportation, power grids, and biological networks, where failures can lead to severe consequences. Research in this area focuses on developing robustness metrics, performing vulnerability analysis, and designing optimization strategies to enhance resilience. Graph learning plays a pivotal role by enabling data-driven approaches that complement analytical and statistical methods. This talk presents our recent state-of-the-art advances in measuring, analyzing, and optimizing network robustness through graph-based techniques, demonstrating their effectiveness in improving reliability and adaptability in complex systems.

Speaker's Bio: Dr. Yang Lou is currently an Associate Professor at the Graduate School of Advanced Science and Engineering, Hiroshima University, Japan. He received his B.E. degree in Electronic and Information Engineering from Xidian University, China, in 2008, and his Ph.D. degree from the Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR China, in 2017. From 2017 to 2025, he held research and academic positions at City University of Hong Kong, Lingnan University, The University of Osaka (Japan), and National Yang Ming Chiao Tung University (Taiwan, China). He has authored more than forty peer reviewed papers in leading IEEE magazines (CIM, CSM) and transactions (TCYB, TNNLS, TNSE, TCASI/II), as well as in international conferences such as ICLR, GECCO, and IJCNN. His h-index is 21 according to Google Scholar. He is a Senior Member of the IEEE and a Fellow of the Higher Education Academy. His research interests include network science, graph learning, and optimization.