Events

Seminar on "Coupling and Clustering of Grid-Forming and Grid-Following Converters in Islanded Microgrids" by Dr Jingxi Yang

Date: 13 March 2026, Friday Time: 4:30 pm Venue: Room FYW-3316, City University of Hong Kong Zoom Meeting ID: 859 8869 4437 Password: 123456 Speaker: Dr Jingxi Yang, City University of Hong Kong Abstract: In an islanded microgrid containing a number of grid-forming and grid-following converters (GFMCs and GFLCs), the GFMCs splits into at least two internally synchro- nized clusters under a sufficiently large transient disturbance, and the GFLCs interact with these clusters to manifest diversified behaviors, e.g., being absorbed into one of the aforementioned clusters, or temporarily joining one of the clusters, or forming a new cluster alone. Such behaviors are dependent on the GFLCs’ injected reactive power, network structure and edge weights. These factors can be adjusted to absorb more GFLCs into the dominant cluster of the microgrid. These findings are verified by a modified IEEE 39-bus power grid. Speaker’s Bio: Jingxi Yang (Member, IEEE) received the B.S. and Ph.D. degrees in electrical engineering from Beijing Jiaotong University, Beijing, China, in 2014 and 2020, respectively. He is currently a Research Fellow with the Department of Electrical Engineering, City University of Hong Kong, Hong Kong. His research interests include the complex nonlinear behavior and stability of grid-connected power electronic converter systems. He was the recipient of the Outstanding Reviewer Award of the IEEE Transactions on Power Electronics in 2021 and 2024, and the Excellent Reviewer Award of the Journal of Modern Power Systems and Clean Energy in 2022. He is a member of the IEEE Power and Energy Circuits and Systems Technical Committee.   WEBINAR WEBSITE: https://www.ee.cityu.edu.hk/~cccn/ https://www.ee.cityu.edu.hk/~cccn/centre-seminars.htm  

Seminar on "Spatio-Temporal Power Flow Forecasting for Cascading Failure Mitigation" by Dr Biwei Li

Date: 6 March 2026, Friday Time: 04:30 PM Venue: FYW-3316, Fong Yun Wah Building, City University of Hong Kong Zoom Meeting ID: 859 8869 4437 Password: 123456 Speaker: Dr Biwei Li, City University of Hong Kong Abstract: Accurate power flow forecasting is crucial for enabling timely interventions to prevent cascading failure events from escalating into large-scale outages. This talk presents a spatio-temporal learning model specifically designed for forecasting power flow redistribution during cascading failure events. The model combines a Transformer-based temporal encoder with a Graph Transformer network to jointly capture the temporal evolution and spatial dependencies within the grid, thereby enhancing robustness under rapidly changing operating conditions. The proposed model is evaluated on the IEEE 118-bus system and compared against several state-of-the-art baselines, demonstrating superior accuracy across short- and long-term forecasting. By accurately forecasting abrupt flow surges across branches, the model supports early identification of vulnerable components and high-risk regions over time. Finally, we introduce a mitigation strategy informed by the power flow forecasting model. Leveraging long-horizon forecasts, the proposed mitigation strategy effectively reduces large outages and circumvents intervention-induced failure. Speaker’s Bio: Biwei Li is currently a research assistant at the City University of Hong Kong, Hong Kong. She received the B.Eng. degree in mechanical engineering from China University of Geosciences, Wuhan, China, in 2015, the M.Eng. degree in control science and engineering from Beihang University, Beijing, China, in 2018, and the Ph.D. degree in electrical engineering from City University of Hong Kong, Hong Kong, in 2026. Her research interests include complex networks, deep learning applications, and robust analysis of power networks. WEBINAR WEBSITE: https://www.ee.cityu.edu.hk/~cccn/ https://www.ee.cityu.edu.hk/~cccn/centre-seminars.htm

Seminar on "MIMO OTA MEASUREMENT" by Prof. QI Yihong

Date: 3 March 2026, Tuesday Time: 03:00 PM Venue: CD634, Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University of Hong Kong Speaker: Prof. QI Yihong , Canadian Academy of Engineering

Seminar on "Homogeneity-Based Design of High-Order Sliding Mode Observers for MEMS Resonators" by Prof. Alexander Triana

Date: 27 February 2026, Friday Time: 04:30 PM Venue: FYW-3316, Fong Yun Wah Building, City University of Hong Kong Zoom Meeting ID: 859 8869 4437 Password: 123456 Speaker: Prof. Alexander Triana, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia Homogeneity-Based Design of High-Order Sliding Mode Observers for MEMS Resonators Prof. Alexander Triana, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia Abstract: This talk presents a robust observer-design framework for MEMS resonators based on high-order sliding modes (HOSM), emphasizing homogeneity as the central tool for both analysis and synthesis. The motivation arises from the well-known limitations of classical first-order sliding mode methods, which, despite their robustness, suffer from chattering, sensitivity to measurement noise, and relative-degree restrictions. The main contribution of the talk is to show how homogeneity provides a unifying framework for HOSM observer design by linking classical, weighted, and geometric homogeneity with finite-time stability analysis of discontinuous systems through homogeneous vector fields and their Filippov regularizations. This perspective is further connected to finite-time and fixed-time stability, as well as robustness properties of ISS/iISS type, highlighting why homogeneity is especially effective for observer synthesis in nonlinear uncertain systems. Overall, the talk argues that homogeneity is not only a theoretical concept, but a practical design principle for constructing finite-time, robust, and implementable observers for MEMS resonator applications. Speaker’s Bio: Alexander Jiménez Triana is a Professor and Researcher with more than twenty years of academic and scientific experience in nonlinear systems and robust control, with a strong emphasis on sliding mode control and active disturbance rejection control. He holds Ph.D. degrees in Electrical Engineering from École Polytechnique de Montréal (Canada) and Universidad de los Andes (Colombia), and he is currently a full-time professor at Universidad Distrital Francisco José de Caldas. He has also held international positions, including a Research Fellow appointment at City University of Hong Kong and an invited professorship at École Polytechnique de Montréal. His work includes peer-reviewed publications, international conference participation, and leadership of research projects in robust control and related engineering applications.   WEBINAR WEBSITE: https://www.ee.cityu.edu.hk/~cccn/ https://www.ee.cityu.edu.hk/~cccn/centre-seminars.htm

Lunar New Year Departmental Lunch Gathering

On 26 February 2026, our Department celebrated the Lunar New Year with a joyful luncheon that brought together Departmental Staff, members from the Departmental Advisory Committee, Outstanding Alumni, and Head’s List Students. The gathering created a lively space for connection and networking, fostering meaningful exchanges across different generations of the EEE community. It was a wonderful opportunity to strengthen bonds and share experiences, which also captured the cultural spirit of the Chinese New Year — a time to come together, share joy, and embrace unity.”

EEE Research Postgraduate Student Orientation

The Department held its RPg Orientation on 6 February 2026, welcoming 14 newly admitted research postgraduate students for Semester 2, 2025/26. The orientation provided an introduction to departmental support and study milestones, with insights shared by Prof. Jovica V. Milanović (Departmental Academic Advisor), Prof. C.Y. Chung (Head of Department), Prof. L.P. Chau (Chair of the Departmental Research Committee), and Prof. Kenneth Lam (Director of Research Postgraduate Studies).

Seminar on "Graph Learning for Network Robustness: Analysis and Optimization" by Dr Yang Lou

Date: 6 February 2026, Friday Time: 04:30 PM Venue: FYW-3316, Fong Yun Wah Building, City University of Hong Kong Zoom Meeting ID: 859 8869 4437 Password: 123456 Speaker: Dr Yang Lou, Hiroshima University, Japan  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.   WEBINAR WEBSITE: https://www.ee.cityu.edu.hk/~cccn/ https://www.ee.cityu.edu.hk/~cccn/centre-seminars.htm

Seminar on "Distributed Optimization Frameworks for Large-Scale Nonlinear Programming in Power Systems " by Dr Xinliang Dai

Date: 3 February 2026, Tuesday Time: 10:00 am Venue: CF303,  The Hong Kong Polytechnic University Speaker: Dr Xinliang Dai

Seminar on "Approaches to modelling and analysis of sustainable, power electronics rich, power networks" by Prof. Jovica V Milanović

Date: 2 February 2026, Monday Time: 3:30 pm Venue: CD301,  The Hong Kong Polytechnic University Speaker: Prof. Jovica V Milanović

Seminar on "Cooperative eco-driving system for mixed traffic on urban roads" by Dr Zhiwei Yang

Date: 30 January 2026, Friday Time: 4:30PM Venue: Online Only Zoom Meeting ID: 383 735 6917 Password: 270831 Cooperative eco-driving system for mixed traffic on urban roads Dr Zhiwei Yang, The Chinese University of Hong Kong, Shenzhen   Abstract: Signalized arterials cause stop-and-go traffic, leading to collisions, delays, energy waste, and discomfort. Connected automated vehicles (CAVs) offer a solution through cooperative eco-driving, but mixed traffic complicates implementation. In this presentation, we introduce rule-based, optimization-based, and reinforcement learning (RL)-based eco-driving systems for CAVs on signalized arterials, balancing safety, efficiency, energy saving, and comfort. These methods include eco-GLOSA, eco-ACC (DDPG, PPO, SAC), and eco-CACC (MADDPG, MASAC). Evaluations use naturalistic pNEUMA trajectory data, benchmarking against human-driven and car-following (CF) models in diverse scenarios. The study comprehensively assesses method effectiveness, platoon stability, and key influencing factors in real-world-inspired conditions, thus delivering actionable and transferable solutions for implementing cooperative automated systems in mixed traffic with current and near-future infrastructure. Speaker’s Bio: Zhiwei Yang is a Postdoctoral Researcher at The Chinese University of Hong Kong, Shenzhen. She received her PhD degree from The University of Queensland in 2025. Her research focuses on intelligent transport systems, urban mobility, reinforcement learning applications for motion control, and High-speed Rail. She has authored multiple papers in Transportation Research Part A, C, and D, Transport Policy, the Transportation Research Board (TRB) Annual Meetings, the IEEE Intelligent Vehicle Symposium (IV), the Australasian Transport Research Forum (ATRF), and the International Conference of Hong Kong Society for Transportation Studies (HKSTS). She also serves as a reviewer for journals such as IEEE Transactions on Intelligent Transportation Systems (TITS), Transportation Research Part C and TRB.   WEBINAR WEBSITE: https://www.ee.cityu.edu.hk/~cccn/ https://www.ee.cityu.edu.hk/~cccn/centre-seminars.htm