Events

PolyU EEE Research Student Conference (PRSC)

Celebrate the success of the PolyU EEE Research Student Conference (PRSC)! Prof. C.Y. Chung, Head of Department, and Prof. Bashir Al-Hashimi from King's College London both gave speeches at the conference. As part of the PolyU EEE Department's initiative to foster academic exchange, this conference provided an opportunity for RPg students who have received conference support to share their work with their classmates. Students presented their published conference papers at this event. Conference detail You can download the conference booklet here. Time: 9:00am Venue: DE306, DE308, DE309 Conference Chair: Prof. M.W. Mak Conference Co-Chair: Guanxi Sun, Kaitao Xue, Chuang Xu, Jiefeng Lin, Feifan Ni Technical Support: Mr. Wai-Lam Hui Committee: Liu Yugui, Huang Yuchun, Zhao Rong, Liu Maoqi, Lu Langran, Wang Xiaoqi, Guo Jingtao, Li Yuanhao, Xie Lingdong, Zhou Zhenhua  

Seminar on "Big-Tech Insights From Cutting-Edge R&D to Career Development in Tencent and Huawei" by Dr Che Haoxuan, Dr Zhou Kang and Ms Zhang Jingyun

Date: 12 July 2025, Saturday Time: 2:00 pm - 4:00 pm Venue: DE301,  The Hong Kong Polytechnic University Speaker: Dr Che Haoxuan, Dr Zhou Kang and Ms Zhang Jingyun, Tencent and Huawei Contact person: Dr WANG Yi (yi-eie.wang@polyu.edu.hk)

Seminar on "Non-faradaic junction sensing" by Prof. WANG Yecheng

Date: 9 July 2025, Wednesday Time: 10:00am Venue: EF312,  The Hong Kong Polytechnic University Speaker: Prof. WANG Yecheng, Sun Yat-sen University

Seminar on "Novel Field Modulation and Magnetically Geared Machines" by Prof. Z.Q. Zhu

Date: 10 June 2025, Tuesday Time: 02:00 pm Venue: FJ301,  The Hong Kong Polytechnic University Speaker: Prof. Z.Q. Zhu, University of Sheffield, UK

Student Sharing with the Head of Unit

EEE Staff Retreat

The Staff Retreat was held in the Hotel ICON on 23 May 2025. The Retreat provided a platform for academic and teaching staff to collaborate and exchange views on key areas, including student engagement, research, teaching and learning, and publicity. Dr K.P. Mark and Mr Kenneth Tam of the Educational Development Centre were also invited to share about Outcome-Based Education this year. Through this annual gathering, more innovative and inspiring ideas are discussed to drive the Department’s future growth and development.

Seminar on "Keynode-Driven Dynamic Mesh Compression" by Dr Truong Nguyen

Date: 22 May 2025, Thursday Time: 11:00 Venue: Room CD634, The Hong Kong Polytechnic University Speaker: Dr Truong Nguyen, University of California San Diego

Seminar on "Multiobjective Complementary Control and Its Application to Mean-Field Games" by Dr Jiapeng Xu

Date: 9 May 2025, Friday Time: 4:30 pm Venue: Room FYW-3316, City University of Hong Kong Zoom Meeting ID: 899 0158 1173 Password: 123456 Speaker: Dr Jiapeng Xu, Hong Kong Polytechnic University   Multiobjective Complementary Control and Its Application to Mean-Field Games Dr Jiapeng Xu, Hong Kong Polytechnic University   Abstract:This presentation introduces an interesting control design paradigm for linear time-invariant systems: multiobjective complementary control (MOCC), in which nominal performance and robustness can be achieved in a complementary way instead of a trade-off. In particular, a state-space solution is first established for a new stabilizing control structure consisting of two independently designed controllers coordinated with a Youla-type operator Q. It is then shown by performance analysis that these two independently designed controllers operate in a naturally complementary way for a tracking control system, due to the coordination function of Q driven by the residual signal of a Luenberger observer. An application of MOCC in robust mean-field games is presented. It is shown that the MOCC framework achieves a complementary mean-field control strategy, in contrast to the existing worst-case strategy.   Speaker’s Bio:Jiapeng Xu received the Ph.D. degree in control science and engineering at the East China University of Science and Technology, China, in 2021. He was a Postdoctoral Fellow with the University of Windsor, Canada, from September 2021 to July 2024, with the University of Victoria, Canada, from July 2024 to September 2024, and with the City University of Hong Kong, China, from October 2024 to January 2025. He is currently a Postdoctoral Fellow in the Department of Applied Mathematics, The Hong Kong Polytechnic University, China. His research interests include networked control, multiobjective complementary control, time-delay systems, and mean-field games. Dr. Xu is an Associate Editor for International Journal of Control, Automation, and Systems. He received the Chinese Association of Automation (CAA) Outstanding Doctoral Dissertation Award in 2022.   WEBINAR WEBSITE: https://www.ee.cityu.edu.hk/~cccn/webinar/

Seminar on "Generating Graphs via Spectral Diffusion" by Prof. Andrea Torsello

Date: 2 May 2025, Friday Time: 12:00pm - 1:00pm Venue: CD634,  The Hong Kong Polytechnic University Speaker: Prof. Andrea Torsello, Ca' Foscari University of Venice Contact person: Prof. ROSSI Luca (luca.rossi@polyu.edu.hk)

Seminar on "Learning to Mitigate Cascading Failure Risk in Power Networks" by Miss Biwei Li

Date: 2 May 2025, Friday Time: 4:30 pm Venue: Room FYW-3316, City University of Hong Kong Zoom Meeting ID: 899 0158 1173 Password: 123456 Speaker: Miss Biwei Li, City University of Hong Kong   Abstract:The Cascade Risk Mitigation Set (CRMS) of branches in a power network refers to specific combinations of branches that enhance the capacity to mitigate cascading failure risk. However, identifying the optimal combination is computationally challenging due to the need for repeated cascading failure simulations and the combinatorial explosion of possible solutions. In this talk, I will introduce a novel framework based on graph neural networks (GNNs) to efficiently identify optimal CRMS solutions. The identification problem involves the risk assessment of cascading failure in the objective function, which can be naturally cast as a graph regression task and effectively addressed using GNNs. Two key techniques are incorporated to improve the prediction performance of GNNs. First, the Bus and Branch Graph Attention Network (BB-GAT) is proposed to jointly encode bus and branch features into the graph representation. Second, a pre-training strategy is adopted to reduce the dependency on large amounts of task-specific data and to improve generalization across different operational states. Finally, a hybrid approach is designed to identify the optimal CRMS. This approach prunes the search space using a statistical method, then employs BB-GAT to recommend high-potential candidate solutions and ultimately determines the optimal one via cascading failure simulations. Experimental results on the IEEE 39-bus and 118-bus systems show that this framework achieves near-optimal performance while significantly improving computational efficiency over traditional algorithms.   Speaker’s Bio:Biwei Li is currently a Ph.D. candidate in the Department of Electrical Engineering 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, and the M.Eng. degree in control science and engineering from Beihang University, Beijing, China, in 2018. Her research interests include complex networks, deep learning applications, and robust analysis of power networks.   WEBINAR WEBSITE: https://www.ee.cityu.edu.hk/~cccn/webinar/