18th IWCFTA

1. Professor C. K. Michael Tse (City University of Hong Kong, China)

Talk Title: Challenges in Network-based Study of Cascading Failure in Power Systems

Abstract: The increasing complexity of modern power grids and their pivotal role in sustaining economic and societal functions necessitate a robust and resilient infrastructure. Power grids, the backbone of modern societies, ensure the continuous flow of energy that powers industries, businesses, and homes. As the energy landscape evolves with the integration of renewable energy sources, artificial intelligence, and complex connectivity with cyber coupling, the power grid faces unprecedented challenges, including cascading failures, cyber vulnerabilities, and the need for efficient resource management. In this talk, we will focus on the study of cascading failure in power systems and how complex network theory can be applied to model the cascade of failure events. We will highlight some challenges in applying complex network methods in light of the physical laws governing electrical system operation and the common inconsistencies arising from simple but subtly invaiid assumptions of failure spreading on electrical networks, leading to unrealistic results and conclusions. We will examine the combined use of deterministic model and stochastic processes to generate realistic simulation models for analyzing cascading failure in power systems.

Biography: Chi K. Michael Tse is currently a Chair Professor of Electrical Engineering at City University of Hong Kong, and concurrently being appointed as Associate Vice-President (Innovation) of the university. His research interests include network applications, nonlinear systems, power electronics, and smart power distribution. He has been awarded a number of research and invention prizes, including the IEEE CASS Charles A. Desoer Technical Achievement Award 2022, Best Paper Prizes from IEEE and other journals, Gold Medals [with Jury’s Commendation] in International Exhibition of Inventions of Geneva (2024, 2013, 2009), IFIA Best Invention Prize and Gold Medal with Jury’s Commendation in Asia Exhibition of Innovations and Inventions 2023, Grand Prize and Gold Medal with Jury’s Commendation in Silicon Valley International Invention Festival 2019, and prizes in other international invention exhibitions. He has been appointed to honorary professorship and distinguished fellowship by several Australian, Canadian and Chinese universities, including Melbourne University, RMIT University, University of Western Australia, University of Calgary, Huazhong University of Science and Technology (Chang Jiang Scholar), etc. He serves and has served as Editor-in-Chief of IEEE Transactions on Circuits and Systems II (2016-2019), IEEE Circuits and Systems Magazine (2013-2016), IEICE Nonlinear Theory and Applications (since 2013); as Editor of IJCTA (2014-2020) and associate editor of a few other IEEE journals. Since 2021, he has served on the Editorial Board of the IEEE Proceedings. He was selected and appointed as IEEE Distinguished Lecturer in 2005, 2010 and 2018. In 2006 he chaired the IEEE CAS Technical Committee on Nonlinear Circuits and Systems. He has also served on a number of IEEE committees including the IEEE Fellows Committee and the IEEE Awards Committee, and chaired the Steering Committee for IEEE Transactions on Network Science and Engineering. He is an IEEE Fellow (elected 2005) and an IEAust Fellow (elected 2009).

2. Professor Neil G. R. Broderick (The University of Auckland, New Zealand)

Talk Title: Symmetry breaking and chaos in nonlinear coupled optical resonators

Abstract: Nanophotonic resonators are becoming increasingly important in numerous applications from quantum computing to Kerr frequency combs. Their small size and thus tightly confined mode volumes allow for high nonlinearities with relatively low photon numbers. They can thus been seen as bridging the gap between the quantum and classical world and allow researchers to find signs of classical chaos in the quantum regime. I will focus on looking at coupling such resonators together either through their linear or nonlinear properties and show how this changes their behaviour. The use of kneading sequences for analysing complex dynamics will be introduced as will a study of the role that symmetry plays in the route to chaos.

Biography: Professor Neil Broderick is a Professor of Physics at the University of Auckland and a founding investigator of the Dodd-Walls Centre for Photonic and Quantum Technologies, one of New Zealand’s Centres of Research Excellence. He received his Ph.D. in Physics from the University of Sydney before spending 14 years at the Optoelectronics Research Centre at the University of Southampton, where he established himself as an internationally recognised expert in nonlinear optics, fibre lasers, and photonics. Since moving to New Zealand, he has held senior academic leadership roles, including Deputy Head of the Department of Physics, and has worked extensively with industry partners such as Buckley Systems and Southern Photonics to translate research into innovation. Professor Broderick has published widely, secured significant international funding, and supervised numerous postgraduate students, reflecting his commitment to research excellence, collaboration, and mentorship.

3. Professor Zhigang Zeng (Huazhong University of Science and Technology, China)

Talk Title: Autonomous intelligent system based on associative memory

Abstract: Inspired by the biological mechanisms of cross-modal associative memory reflexes, this study simulates the formation of primary associative memories of multisensory inputs in the primary sensory cortex. It constructs an associative memory storage-retrieval model for the sensory cortex and proposes a memristive neural network framework for bidirectional multisensory associative memory. This framework enables simultaneous implementation of intra-modal and cross-modal associations at the circuit level. Furthermore, leveraging multisensory associations in higher brain regions such as the thalamus and amygdala, circuits are designed to simulate human-like emotion generation and evolution. The aim is to endow robots with the ability to perceive and express emotions, thereby enhancing their applications in autonomous intelligent systems such as human-machine interaction systems.

Biography: Professor Zhigang Zeng is a full professor at Huazhong University of Science and Technology (HUST) and the Director of the Key Laboratory of Image Processing and Intelligent Control under the Ministry of Education. He received his Ph.D. degree in Systems Analysis and Integration from HUST in June 2003. He subsequently conducted postdoctoral research at The Chinese University of Hong Kong and the University of Science and Technology of China. He has served as an editorial board member for several international journals, including IEEE Transactions on Neural Networks, IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Cognitive Computation, Neural Networks, Applied Soft Computing, Acta Automatica Sinica, Control Engineering of China, Journal of Systems Engineering and Electronics, and Control Theory & Applications. He has received multiple prestigious awards, including the First Prize of Natural Science Award of the Ministry of Education for Outstanding Achievement Award for Research in Institutes of Higher Education, the First Prize of Hubei Province Natural Science Award, the First Prize of Hubei Province Science and Technology Progress Award, and the Second Prize of the National Science and Technology Progress Award.

4. Professor Zhongrui Wang (Southern University of Science and Technology, China)

Talk Title: Memristive computing: From systems to devices

Abstract: The advancement of AI lies on data, model, and hardware. However, traditional digital hardware faces significant challenges. These include the end of Moore’s Law due to transistor scaling limits and the von Neumann bottleneck arising from physically separated memory and processing units. Memristors are deemed a solution for efficient and scalable deep learning, which also witnesses tremendous efforts towards commercialization. In this talk, we will discuss how to advance memristive computing at different levels: systems/applications and circuits. At the systems/applications level, our focus is on hardware-software codesign to turn the inevitable memristor nonidealities (such as stochasticity and expensive programming) into advantages. We explore applications in graph learning for AI4S [1,2] and few-shot to zero-shot learning [3], and a unified representation/architecture for edge [4]. At the circuit level, we devise circuits that exploit the in-memory processing of analog signals, which physically implements dynamic ANNs and SNNs [5,6], ODE/SDE solvers for diffusion and digital twins [7,8] as well as accurate neural implicit representation.
References
1. S. Wang et al., Nat. Mach. Intell. 5, 104 (2023).
2. M. Xu et al., Nat. Comp. Sci. (2025).
3. N. Lin et al., Nat. Comp. Sci. 5, 37 (2025).
4. S. Wang et al., Nat. Comm. 16, 960 (2025).
5. Y. Zhang et al., Sci. Adv. 10, eado1058 (2024).
6. B. Wang et al., Sci. Adv. 11, eads5340 (2025).
7. J. Yang et al., 70th Annual IEEE International Electron Devices Meeting (IEDM), Dec 2024, San Francisco, USA.
8. H. Chen et al., Sci. Adv. 11, eadr7571 (2025).

Biography: Dr. Zhongrui Wang is a tenured associate professor at the School of Microelectronics at Southern University of Science and Technology, an awardee of the NSFC Excellent Youth Fund (Hong Kong and Macau), and a Clarivate Highly Cited Researcher. Prior to joining SUSTech, he was an assistant professor in the Department of Electrical and Electronic Engineering at the University of Hong Kong. He earned his Bachelor's degree (First Class Honors) and Ph.D. from Nanyang Technological University in Singapore. Dr. Wang's research primarily focuses on novel memristive AI hardware and algorithm co-design. He has published papers as a corresponding or first author in journals such as Nature Reviews Materials, Nature Materials, Nature Electronics (4 papers), Nature Machine Intelligence (2 papers), Nature Computational Science (2 papers), Nature Communications (3 papers), Science Advances (3 papers), as well as conferences like DAC (6 papers), ICCAD (2 papers), Neurips, ICCV and IEDM. His work has received over 21,000 citations on Google Scholar (h-index of 51) and has been featured in over 40 news outlets, including IEEE Spectrum, Scientific American, Science Daily, Phys.org, and ACM Communications. Dr. Wang serves on the editorial boards of journals such as Materials Today Electronics, Frontiers in Neuroscience, and APL Machine Learning.

5. Professor Mo Chen (Changzhou University, China)

Talk Title: Modeling, Dynamics, and Implementation of Memristive Systems: From Oscillation Circuits to Neuromorphic Circuits

Abstract: The memristor has innate nonlinearity and plasticity, which assists the revolutionized design of nonlinear circuits and systems and opens new frontiers in chaos generation and neuromorphic engineering. This talk presents a comprehensive overview of our research group’s recent advancements in modeling, dynamics, and implementation of memristive systems, tracing from oscillation circuits to neuromorphic circuits. We begin by summarizing our foundational work on modeling and dynamics analysis of memristive chaotic circuits, emphasizing the distinctive initial-dependent nonlinear phenomena, along with their synchronization control in coupled networks. Thereafter, we present novel designs for bio-inspired neuromorphic circuits by leveraging the inherent properties of the memristor. The theoretical insights and design methodologies gleaned from nonlinear circuits inform the development and comprehension of memristor-driven neuromorphic circuits, effectively bridging the gap from fundamental dynamic principles to sophisticated brain-inspired computing paradigms.

Biography: Mo Chen is a professor at the Wang Zheng School of Microelectronics, Changzhou University, Changzhou, China. Her research interest mainly focuses on memristor and its application circuits, and other nonlinear circuits and systems. She is a core member of “Memristor circuit and intelligent network (MCIN)” and this group won the 2019 excellent scientific and technological innovation team of Jiangsu province. She has authored about 120 SCI-indexed journal papers, including 3 hot papers, 13 highly cited papers, and was honored with “The IET Premium Awards 2018”. She has obtained funding from multiple national and provincial research programs, been awarded two First Prizes and one Third Prize in the Jiangsu Provincial Educational Science Research Achievement Awards, and was selected as the Highly Cited Researcher 2022 in Cross-Field.