Events

EEE Staff Retreat

The Staff Retreat, held at Harbour Plaza Metropolis, successfully concluded as the first gathering following the merger. Attended by academic/teaching and some administrative staff members, the Retreat provided a platform for collaboration and idea-sharing on key focus areas. Discussions revolved around RAE preparation, promotion strategies, student engagement initiatives, and teaching and learning innovations.  Breakout sessions allowed for in-depth discussions, leading to the identification of strategies and action plans.  The Department looks forward to implementing the discussed initiatives and sustaining the positive momentum for future growth.

Seminar on "Design of Joint Source-Channel Coding Schemes Based on DP-LDPC Codes and Spatially-Coupled DP-LDPC Codes" by Ms Jia Zhan

Date: 19 April 2024, Friday Time: 4:30pm Venue: CD634, The Hong Kong Polytechnic University Zoom Meeting ID: 891 2966 7141 Password: 123456 Speaker: Ms Jia Zhan, The Hong Kong Polytechnic University   Design of Joint Source-Channel Coding Schemes Based on DP-LDPC Codes and Spatially-Coupled DP-LDPC Codes Ms Jia Zhan, The Hong Kong Polytechnic University   Abstract: The joint source-channel coding (JSCC) technique, which can jointly design source and channel codes by exploiting source statistics and channel information to achieve optimal overall error performance, is superior to the separate source-channel design under scenarios with finite code length. Different JSCC schemes based on double channel codes, such as low-density parity-check (LDPC) and polar codes, have been proposed. This seminar focuses on the JSCC schemes based on LDPC codes, and will introduce a new type of JSCC scheme based on double protograph-based LDPC (DP-LDPC) codes and a new class of JSCC scheme based on spatially coupled DP-LDPC codes.   Speaker’s Bio: Ms Jia Zhan received a B.Sc. degree in electronic information engineering from Yantai Nanshan University, Yantai, China, in 2013 and received an M.Sc. degree in electronic and communication engineering from Xiamen University, Fujian, China. Ms Zhan is currently a Ph.D. student at the Department of Electrical and Electronics Engineering, The Hong Kong Polytechnic University. Her current research interest is joint source-channel coding.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/  

Seminar on "Strengthening Critical Power Network Branches for Cascading Failure Mitigation (rehearsal talk for IEEE ISCAS 2024)" by Miss Biwei Li

Date: 12 April 2024, Friday Time: 4:30pm Venue: YEUNG G7603, City University of Hong Kong Zoom Meeting ID: 955 7075 2299 Password: 123456 Speaker: Miss Biwei Li, City University of Hong Kong   Strengthening Critical Power Network Branches for Cascading Failure Mitigation (rehearsal talk for IEEE ISCAS 2024) Miss Biwei Li, City University of Hong Kong   Abstract:Strengthening critical components is considered one of the most essential means to enhance the robustness of power networks against cascading failure. This talk discusses an iterative method to strengthen the critical power network branches identified from a tailor-made failure propagation graph. To construct the failure propagation graph, we generate numerous cascading failure trees, capturing both temporal and spatial features of failure propagation processes from cascading failure simulations. The constructed graph is a weighted and directed graph that is able to characterize failure propagation patterns in a power network. By employing weighted eigenvector centrality to assess node criticality, we iterate through the graph to identify the most significant nodes and subsequently determine the critical power network branches to be strengthened. Simulation results in the IEEE 118 bus system demonstrate the effectiveness and efficiency of our strategy in mitigating cascading failure compared to existing methods.   Speaker’s Bio:Biwei Li graduated from Beihang University. She is currently a PhD candidate in the Department of Electrical Engineering at CityU. Her research focus is in complex network applications to robustness analysis of power systems.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/

Welcoming Tea Reception for First-Year Students 2024

The Welcoming Tea Reception for First-Year Students 2024 was held by the Department at Hotel ICON Silverbox Ballroom on 6 April 2024. Over 200 participants, including students, teachers, and alumni attended the event. The aim of the event was to introduce year-one students to the EEE Department and its department members; let the year-one students to know more of the comprehensive range of student activities and clubs etc. By pairing students with alumni and professors, interaction in between was warm and supportive. The EEE Welcoming Tea Reception was an important event to kickstart their journey in our department.

Seminar on "Design of Wireless In-Wheel Motor Drive With S/CP Compensation " by Mr Felix Chen

Date: 3 April 2024, Wednesday Time: 4:30pm Venue: YEUNG Y5-202, City University of Hong Kong Zoom Meeting ID: 955 7075 2299 Password: 123456 Speaker: Mr Felix Chen, City University of Hong Kong   Design of Wireless In-Wheel Motor Drive With S/CP Compensation (rehearsal talk for IEEE ISCAS 2024) Mr Felix Chen, City University of Hong Kong   Abstract:This talk introduces a wireless in-wheel motor drive system based on the series/capacitor-parallel (S/CP) compensation topology. Despite the structural similarity with the conventional series/series-parallel (S/SP) circuit, the S/CP compensation embraces a different design concept to enhance the voltage gain flexibility. The study examines the input impedance and voltage gain characteristics of the system across all load and misalignment conditions. Subsequently, a novel design method is proposed to facilitate soft switching and ensure compliance with the bus voltage requirement. Consequently, the proposed design method could avoid wireless communication and additional DC/DC converters. Finally, a 600 W prototype is constructed to validate the above analysis, yielding a remarkable maximum efficiency of 96.81%.   Speaker’s Bio:Xin Felix Chen graduated from Nanjing University of Aeronautics and Astronautics. He joined CityU in 2021 as a Research Assistant and later became a PhD candidate in the Department of Electrical Engineering. His research focus is in power electronics, motor drives and wireless power transfer.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/

Seminar on "New Technology of Real Time Simulator and Its Applications" by Dr. Yi Zhang

Date: 3 April 2024, Wednesday Time: 4:30pm Venue: BC404, The Hong Kong Polytechnic University Speaker: Dr. Yi Zhang, RTDS Technologies Inc.

Women in Electrical and Electronic Engineering (WiEEE) Gathering for Postgraduate Students and Research Staff

The Women in Electrical and Electronic Engineering (WiEEE) Gathering for Postgraduate Students and Research Staff was held by the Department at the PolyU Staff Club Restaurant, U.Green, on 22 March 2024. This activity brought together over 40 participants, including female postgraduate students, academic and research staff.   The event featured guest speakers Prof. Winnie Ye, Professor at Carleton University and Chair-Elect of IEEE Women in Engineering Committee, and Dr Qian Li, Associate Professor and Deputy Dean of School of Electronic and Computer Engineering at Peking University. Prof. Ye and Dr Li shared their experiences as women engineers and the professional paths in academia. Their insights provided valuable inspiration for the participants in developing their careers in research and engineering.

Seminar on "Emergence of Cooperation via Reinforcement Learning in Multiagent Systems " by Prof. Zhihai Rong

Date: 22 March 2024, Friday Time: 4:30pm Venue: CD634, The Hong Kong Polytechnic University Zoom Meeting ID: 955 7075 2299 Password: 123456 Speaker: Prof. Zhihai Rong, Donghua University, Shanghai   Emergence of Cooperation via Reinforcement Learning in Multiagent Systems Prof. Zhihai Rong, Donghua University, Shanghai   Abstract: Evolutionary game theory provides a powerful framework to investigate the decision process and the emergence of cooperation among rational agents in populations. The learning process is the core of evolutionary game theory. The celebrated replicator dynamics characterizes agents’ strategy evolving and learning processes, and highlights the influence of selection in populations game through a continuous differential equation, whose stable equilibrium points correspond to evolutionary stable states. Multi-agent reinforcement learning is another effective computational method to study evolutionary games theory. The trial-and-error learning process in reinforcement learning is similar to the evolutionary process in biology. The classical Q-learning algorithm can built a bridge between the exploitation-exploration mechanism of reinforcement learning and the selection-mutation mechanism of evolutionary game theory. In this talk, I will analyze the nonlinear dynamics of Q-learning like algorithms through the perspective of evolutionary dynamics, and reveal the potential learning mechanism to promote the emergence of cooperation in infinite and finite populations with memory strategies, which may yield some insight into achieving cooperative machine agents and understanding the evolution of machine behavior.   Speaker’s Bio: Dr Zhihai Rong obtained his Bachelor and Master degrees from Harbin Institute of Technology and Ph.D degree from Shanghai Jiaotong University, all in Control Science and Engineering. He was a Hong Kong Scholar with PolyU. Now he is a professor in the Department of Automation, Donghua University, Shanghai. His research interests include complex networks, evolutionary game dynamics and mechanism design. He is the author of over 60 papers in peer reviewed scientific journals and international conferences, including IEEE Tran. CAS-II, IEEE Tran. Cybernetics, Automatica, Physical Review E, Europhysics Letters (EPL), Chaos, ISCAS and IFAC, received more than 3000 citations with h-index 29.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/

Seminar on "Intelligent Perception and Trustworthy Navigation for Ground Vehicles in Challenging Environments" by Dr Rui Song

Date: 15 March 2024, Friday Time: 4:30pm Venue: CD634, The Hong Kong Polytechnic University Zoom Meeting ID: 383 735 6917 Password: 274320 Speaker: Dr Rui Song, The Hong Kong Polytechnic University   Intelligent Perception and Trustworthy Navigation for Ground Vehicles in Challenging Environments Dr Rui Song, The Hong Kong Polytechnic University   Abstract:The advancement of Simultaneous Localization and Mapping (SLAM) technology, along with the measurement technique, has greatly enhanced the applications of Autonomous Driving and Unmanned Ground Vehicles in modern society. However, the current strategy faces challenges when operating in some complex environments, particularly those with uneven terrain and sparse features. In this talk, the latest developments will be reviewed with an emphasis on the environment perception approach and an integrated navigation system framework. After that, some of our recent works on LiDAR-based perception and Kalman filter-based estimators will be presented, so as to improve the estimation accuracy of vehicle states and navigation trustworthiness. In addition, simulation and field tests were implemented to validate the effectiveness of the methods. In the future, the designed framework will be extended to encompass V2X applications and address safety concerns within digital twin-based systems.   Speaker’s Bio: Rui Song is currently a post-doctoral research associate at the Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University. He received the Ph.D. degree in Instrument Science and Technology from Southeast University in 2018. He was a Visiting Scholar at the Department of Electronic, Electrical and Systems Engineering, University of Birmingham, U.K. from 2016-2017. His research interests include multi-sensor fusion and intelligent navigation for unmanned systems.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/

Seminar on "What Contributes More to the Robustness of Heterophilic Graph Neural Networks?" by Mr Junyuan Fang

Date: 8 March 2024, Friday Time: 4:30pm Venue: YEUNG Y5-202, City University of Hong Kong Zoom Meeting ID: 955 7075 2299 Password: 123456 Speaker: Mr Junyuan Fang, City University of Hong Kong What Contributes More to the Robustness of Heterophilic Graph Neural Networks? Mr Junyuan Fang, City University of Hong Kong   Abstract:In recent years, graph neural networks (GNNs) have gained significant attention due to their outstanding performance on graph-related tasks by utilizing neighborhood aggregation. However, traditional GNNs are primarily designed based on the homophily assumption, which means that they show poor performance on heterophilic networks where dissimilar nodes prefer to connect. To address this issue, several heterophilic GNNs have been proposed that employ techniques such as extending local neighbors and improving GNN architectures. From another perspective, recent studies have shown that, unlike homophilic GNNs, heterophilic GNNs exhibit higher robustness against graph adversarial attacks. In these attacks, the attackers try to inject small perturbations into the graph. Therefore, in this study, we delve into the core designs of heterophilic GNNs, including high-order neighbor, potential neighbor, ego-neighbor separation, and inter-layer combination designs. We further analyze the influence of these key designs on the robustness of GNNs. To compare the impact of different designs on baseline and real-world GNN models, we conducted comprehensive experiments. The findings of this work can serve as a reference for future studies aiming to design more robust and universal GNNs.   Speaker’s Bio:Junyuan Fang received the B.Eng. degree in software engineering from the Guangdong University of Technology, Guangzhou, China, in 2018, and the M.Eng. degree in software engineering from Sun Yat-sen University, Guangzhou, in 2020. He is currently pursuing the Ph.D. degree with the Department of Electrical Engineering, City University of Hong Kong. His current research interests include robustness analysis and optimization, applications of network science, and graph mining.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/