Invited Speakers
1. Professor Stefano Boccaletti (The Institute of Complex Systems of the Italian CNR, Italy，欧洲科学院院士、意大利国家科学院复杂系统研究所常务研究主任)
Talk Title: The transition to synchronization of networked dynamical systems
Abstract: From brain dynamics and neuronal firing, to power grids or financial markets, synchronization of networked dynamical units is the collective behavior characterizing the normal functioning of most natural and manmade systems. As a control parameter (typically the coupling strength in each link of the network) increases, a transition occurs between a fully disordered and gaseous-like phase (where the units evolve in a totally incoherent manner) to an ordered or solid-like phase (in which, instead, all units follow the same trajectory in time). The transition between such two phases can be discontinuous and irreversible, or smooth, continuous, and reversible. The first case is known as Explosive Synchronization, and refers to an abrupt onset of synchronization following an infinitesimally small change in the control parameter. The second case is the most commonly observed one, and corresponds to a second-order phase transition, resulting in intermediate states emerging in between the two phases. Namely, the path to synchrony is here characterized by a sequence of events, where structured states emerge made of different functional modules (or clusters), each one evolving in unison. In my talk, I will assume that, during the transition, the synchronous solution of each cluster does not differ substantially from that characterizing the solid-like phase and, under such an approximation, I will introduce a (simple, effective, and limited in computational demand) method which is able to: i) predict the entire sequence of events that are taking place during the transition; ii) identify exactly which graph's node belongs to each of the emergent clusters, and iii) providea well approximated calculation of the critical coupling strength value at which each of such clusters is observed to synchronize. I will demonstrate that, under the assumed approximation, the sequence of events is in fact universal, in that it is independent of the specific dynamical system operating in each network's node and depends, instead, only on the graph's structure.
Biography: Stefano Boccaletti received the PhD in Physics at the University of Florence on 1995, and a PhD honoris causa at the University Rey Juan Carlos of Madrid on 2015. He was Scientific Attache’ of the Italian Embassy in Israel during the years 2007-2011 and 2014-2018. He is currently Director of Research at the Institute of Complex Systems of the Italian CNR, in Florence. His major scientific interests are i) pattern formation and competition in extended media, ii) control and synchronization of chaos, and iii) the structure and dynamics of complex networks. He is Editor in Chief of the Journal “Chaos, Solitons and Fractals” (Elsevier) from 2013, and member of the Academia Europaea since 2016. He was elected member of the Florence City Council from 1995 to 1999. Boccaletti has published 352 papers in peer-reviewed international Journals, which received more than 35,000 citations (Google Scholar). His h factor is 70 and his i-10 index is 227. With more than 12,300 citations, the monograph “Complex Networks: Structure and Dynamics”, published by Boccaletti in Physics Reports on 2006 converted into the most quoted paper ever appeared in the Annals of that Journal.
2. Professor Malay Banerjee （Indian Institute of Technology Kanpur, India）
Talk Title: Numerical continuation to detect Turing pattern outside the Turing domain
Abstract: The Turing instability of coexisting homogeneous steady states in reaction-diffusion systems for interacting population models often leads to heterogeneous stationary patterns. However, the existence and detection of such heterogeneous solutions depend on the stability of non-constant steady states associated with the corresponding boundary value problem. The main objective of this talk is to discuss the numerical detection of stationary Turing patterns beyond the Turing instability domain and to identify the involved bifurcations through the numerical continuation technique. The illustration will be based on a spatiotemporal prey-predator model with saturated cooperative hunting among the predators. As a future direction of research, we will discuss the existence of stationary patterns after long transients due to the presence of the Belyakov-Devaney transition.
References:
[1] S. Dey, M. Banerjee and S. Ghorai: Bifurcation analysis and spatio-temporal patterns of a prey-predator model with hunting cooperation, Int. J. Bif. Chaos, 32(11), 2250173, 2022.
[2] S. Dey, S. Ghorai and M. Banerjee: Analytical detection of stationary and dynamic patterns in a prey-predator model with reproductive Allee effect in prey growth, J. Math. Biol., 87, 21, 2023.
Biography: Prof. Malay Banerjee is a Professor in the Department of Mathematics & Statistics at IIT Kanpur, India, currently holding the position of Shri Deva Raj Chair Professor. Prof. Banerjee received his Ph.D. in Applied Mathematics from the University of Calcutta under the guidance of Prof. C. G. Chakrabarti. His academic journey includes teaching stints at Presidency College, Kolkata, and Scottish Church College, Kolkata, before joining IIT Kanpur in 2008. His broad research interests lie in the realms of Nonlinear Dynamics, Mathematical Ecology, and Epidemiology. Prof. Banerjee is actively involved in the academic community and has published several research articles in various reputed journals, which are well-cited. He also serves as an Associate/Executive/Subject Editor for several renowned journals, including Applied Mathematics and Computation, Applied Mathematical Modelling, International Journal of Bifurcation and Chaos, Mathematical Biosciences, Mathematical Biosciences and Engineering, and Mathematical Modelling of Natural Phenomena.
3. Professor C. K. Michael Tse (City University of Hong Kong, China)
Talk Title: The Evolving Power Grid Towards a Greener Future
Abstract: As prompted by the increasing use of renewable sources and the quest for higher performance in the control of power conversion, the use of power electronics in generation and distribution systems has increased significantly in recent years,. Interactions of power electronics systems and conventional synchronous machines' dynamics would inevitably cause stability and robustness concerns, which can be understood from the conventional control viewpoint and the coupling effects among interacting dynamical systems of varying stability margins (or transient performances). In this talk, we discuss the various circuits and systems problems of power electronics penetration into power grids and the implications on the continuous evolution of the power grids.
Biography: C K Michael Tse received the BEng (Hons) degree in electrical engineering and the PhD degree from the University of Melbourne, Australia. He is currently Associate Vice President, Director of Academy of Innovation, and Chair Professor of Electrical Engineering with City University of Hong Kong. His research interests include power electronics, nonlinear systems, and complex network applications. Prof. Tse was the recipient of a number of research and industry awards, including the IEEE CASS Charles A. Desoer Technical Achievement Award in 2022, Prize Paper Awards by IEEE Transactions on Power Electronics in 2001, 2015, 2017, 2021 and 2022, six Gold Medals and Grand Prizes at the international invention exhibitions, and a number of recognitions by the academic and research communities, including honorary professorship and fellowship by several Chinese, Canadian and Australian universities, including Melbourne University, RMIT University, University of Western Australia, Calgary University, Huazhong University of Science and Technology (being Chang Jiang Scholar Chair). He was the Editor-in-Chief for the IEEE Transactions on Circuits and Systems II from 2016 to 2019 and IEEE Circuits and Systems Magazine from 2012 to 2015, and on the editorial boards of a few other IEEE journals. He has been ranked among the top 2% scientists by citation in recent Stanford ranking studies, and was ranked 32nd worldwide and 1st in Hong Kong in the EEE subfield for his lifelong career impact. He was elected as an IEEE Fellow in 2005.
4. 吕金虎教授（北京航空航天大学）
Talk Title: 智能感知与协同控制新进展
Abstract: Artificial intelligence technology has a profound impact on the development of systems and control sciences. Large scale complex group behavior has emerged group intelligence beyond individual ability through individual intelligence stimulation and group intelligence aggregation, which has become one of the important models to solve large-scale complex problems in uncertain environment. Firstly, this report briefly introduces the development history and scientific frontiers of swarm intelligence, as well as the typical applications. Subsequently, some new developments in swarm intelligence perception and cooperative control will be introduced. Finally, the development prospects of intelligent perception and cooperative control technology are discussed.
人工智能技术深刻影响着系统与控制科学的发展。大规模复杂群体行为通过个体智慧激发和群体智慧汇聚涌现出了超越个体能力的群体智能，成为解决不确定环境中大规模复杂问题的重要模式之一。本报告简要介绍群体智能的发展历程与科学前沿，以及群体智能的典型应用；随后介绍群体智能感知与协同控制的一些新进展；最后展望智能感知与协同控制技术的发展前景。
Biography: Professor Jinhu Lü is the Vice-President for scientific research with Beihang University, he is the president of the National Alliance of Science & Technology Leadership, and the vice president of Chinese Institute of Command and Control. He is also the executive director of China Automation Society. He is the Fellow of IEEE, CAA, ORSC, and CICC. His current research interests include industrial Internet, cooperation control, and network dynamics. He is a Leading Scientist of Innovative Research Groups of National Natural Science Foundation of China, a Chief scientist of key project of national industrial Internet innovation and development project, and a Chief Scientist of National Key Research and Development Program of China. Prof. Lü was a recipient of the prestigious Ho Leung Ho Lee Foundation Award in 2015, the National Innovation Competition Award in 2020, the State Natural Science Award three times from the Chinese Government in 2008, 2012, and 2016, respectively, the Guanghua Engineering Science and Technology Award of Chinese Academy of Engineering, the Young Scientist Award of Chinese Academy of Sciences, the National Natural Science Fund for Distinguished Young Scholars Award, and the Co-Editor-in-Chief of IEEE TII. He was the General Co-Chair of IECON 2017.
吕金虎，北京航空航天大学副校长、国家杰青/创新群体学术带头人、IEEE/CAA/ORSC/CICC Fellow。全国科技创新领军人才联盟理事长、中国指挥与控制学会副理事长、中国自动化学会常务理事。从事工业互联网、协同控制等研究，主持国家工业互联网重大项目(2.5亿)、国家重点研发计划项目等，WoS总他引2万余次，授权发明专利150余项，入选全球前2%顶尖科学家/终生科学影响力榜单、全球高被引科学家。曾获3项国家自然科学二等奖，全国创新争先奖、何梁何利科技进步奖、国家级教学成果二等奖、中国工程院光华青年奖、中国科学院青年科学家奖等。
5. 王青云教授 (北京航空航天大学/宁夏大学)
Talk Title: A New Paradigm of Motor Control Integrating Neurodynamics Computation（融合神经动力学计算的运动控制的新范式）
Abstract: Current research on artificial intelligence paradigms for controlling robotic arms primarily focuses on the training and execution of specific tasks, lacking the rapid adaptability to dynamic environments, especially in cognition, decision-making, and motor control, where performance is not synchronized with that of humans. The main reason is the lack of clarity on the working principles of the neural system for motor control. Starting from the physiological motor control circuit of the human central nervous system, a motor control model based on brain neurons and nuclei is established to explore the mechanisms by which humans generate various movements through the nervous system, laying a foundational theoretical basis for the research of "Brain-Inspired Robots." This report, based on the biological nervous system, first introduces the structure and function of the motor control circuit including the brain nervous system, spinal cord nervous system, and musculoskeletal system. Then, focusing on the error-induced STDP mechanism in the cerebellum and the dopamine-induced synaptic plasticity mechanism in the cortex, it explores the role of cerebellar supervised learning and cortical reinforcement learning in arm movement control through dynamic modeling of motor circuits and the implementation of motor control, revealing the mechanism behind the high adaptability and flexibility of humans in unknown environments.
目前以人工智能范式控制机械臂的研究主要集中在特定任务的训练和执行上，缺乏对动态环境的快速适应能力，特别是在认知，决策，和运动控制方面无法取得和人类同步的表现，主要的原因是对运动控制的神经系统工作原理尚未清晰。从人类中枢神经系统的生理运动控制环路出发，建立以大脑神经元和核团为基础运动控制模型，探究人类通过神经系统产生多种运动的机制，为“脑启发机器人”的研究奠定原理性的基础理论。本次报告基于生物神经系统，首先介绍包括脑神经系统，脊髓神经系统和肌骨系统的运动控制环路结构和功能，然后针对小脑中误差诱导的STDP机制和皮层中多巴胺诱导的突触可塑性机制，从运动环路动力学建模和运动控制的实现探究小脑监督学习和皮层强化学习在手臂运动控制中的作用，揭示人类在未知环境下存在高适应性和灵活性的机理。
Biography: Qingyun Wang is a full professor of Dynamics and Control at Beihang University, a doctoral supervisor, and holds several key positions at Ningxia University, including the Academic Vice President, the Dean of the School of Mathematics and Statistics. He is a recipient of the National Science Fund for Distinguished Young Scholars and the Changjiang Scholar Chair Professor of the Ministry of Education. Prof. Wang's primary research interests include neurodynamic computation, intelligent dynamics, and control theory and their applications. He has led over 20 national scientific research programs, including the National Science Fund for Distinguished Young Scholars and key projects of the National Natural Science Foundation of China. He has published more than 180 SCI-indexed papers and has been recognized as a highly cited scholar in China by Elsevier from 2020 to 2023. His awards include the Supported by Program for New Century Excellent Talents in University, the Second Prize in Natural Science by the Ministry of Education, the Second Prize in Natural Science by Beijing Municipality, the Seventh Youth Science and Technology Award of Inner Mongolia Autonomous Region, and the Second Prize in Natural Science by the Chinese Society of Theoretical and Applied Mechanics. He holds several leadership roles in academic societies, including the Vice Chair of the Dynamics and Control Committee of the Chinese Society of Theoretical and Applied Mechanics for the 10th and 11th terms, the Vice Chair of the Rational Mechanics and Mathematical Methods in Mechanics Committee, a director of the Beijing Society of Mechanics, the Vice Chair of the Nonlinear Vibration Committee of the Chinese Vibration Engineering Society, a standing committee member of the Swarm Intelligence and Collaborative Control Committee of the Chinese Command and Control Society, a member of the Biomedical Engineering and Biomedical Control Engineering Professional Committee, an academic committee member of Beihang University, the Deputy Director of the Academic Committee of Ningxia University, and the Director of the Ningxia Basic Mathematical Discipline Research Center. Prof. Wang is also an Associate Editor for the International Journal of Bifurcation and Chaos, a special editor for Applied Mathematics and Mechanics, the Deputy Editor-in-Chief for Cognitive Neurodynamics, the Executive Editor-in-Chief for the Journal of Ningxia University (Natural Science Edition).
王青云，北京航空航天大学动力学与控制学科责任教授，博士生导师，宁夏大学学术副校长、数理信息学部部长、数学统计学院院长、科学与技术学院副院长，国家杰出青年科学基金获得者，教育部“长江学者”特聘教授。北京市脑重大疾病研究院兼职教授。主要从事神经动力学、智能动力学与控制理论和应用研究，主持国家杰出青年科学基金、国家自然科学基金重点项目等国家级科研计划项目20余项；发表SCI论文180余篇，连续4年2020-2023爱思唯尔中国高被引学者，获教育部新世纪优秀人才支持计划、教育部自然科学二等奖、北京市自然科学二等奖、内蒙古自治区第七届青年科技奖、中国力学学会自然科学二等奖。任中国力学学会第十、十一届动力学与控制专业委员会副主任，神经动力学专业组组长，中国力学学会理性力学和力学中的数学方法专业委员会副主任，北京市力学学会理事，中国振动工程学会非线性振动专业委员会副主任，中国指挥与控制学会网络科学与工程专业委员副主任，中国指挥与控制学会集群智能与协同控制专委会常务委员，生物控制和生物医学工程专业委员会委员，北京航空航天大学校学术委员会委员，宁夏大学校学术委员会副主任，宁夏数学基础学科研究中心主任。国际杂志International Journal of Bifurcation and Chaos的Associate Editor，Applied Mathematics and Mechanics特约编委，Cognitive Neurodynamics副主编，宁夏大学学报（自然科学版）常务副主编，北京航空航天大学学报编委，高等教育出版社出版的《网络科学与工程丛书》编委。
6. 王丽丹教授（西南大学）
Talk Title: In-memory Computing Memristor Device and its AI Accelerators（存算一体忆阻器件及其AI加速器）
Abstract: As artificial intelligence algorithms demand more computational power and memory, the issues of power consumption and latency inherent in the traditional separation of processing and memory in chip architectures are becoming more apparent. In the post-Moore's Law era, it's crucial to explore new avenues for driving continuous growth in computational power, from the device level to architectures and algorithms. Memristors, recognized as the fourth fundamental passive electronic component alongside resistors, capacitors, and inductors, offer unique advantages in multi-bits storage and in-memory computing. These properties can greatly enhance the computational density and energy efficiency of AI chips, making them particularly promising for large model inference tasks. This report delves into the potential of memristors and neuromorphic chips, covering the development of in-memory computing memristors, in-sensor computing optoelectronic memristors, as well as memristor-based AI accelerators and their application in deep learning algorithms.
随着人工智能算法对算力和内存需求的不断提升，芯片的存算分离架构带来的功耗和时延问题日益凸显。后摩尔时代亟需从器件、架构、算法等各层次为算力持续增长提供新的驱动力。忆阻器被公认为是与电阻、电容和电感并列的第四种基本无源电子元件，其多比特存储和存算一体特性能够大幅度提高AI芯片的计算密度和能效，特别是在大模型推理任务中具有广阔的应用前景。本报告围绕忆阻器件与类脑芯片，介绍存算一体忆阻器、感存算一体光电忆阻器的制备、忆阻器AI加速器及其在深度学习中的应用。
Biography: Lidan Wang is a professor and PhD supervisor at the College of Artificial Intelligence, Southwest University. She is recognized as an Innovative Leading Talent by Chongqing Talents and a Chongqing Young and Middle Aged Backbone Teacher. She serves as the director of the Chongqing Key Laboratory of Brain-inspired Computing and Intelligent Chips. Additionally, she holds positions as the Secretary-General of the Chongqing Association for Artificial Intelligence and Director of the Chongqing Youth Science and Technology Leading Talent Association. Her primary research areas is artificial intelligence, including deep learning, neuromorphic computing, memristor devices and chips, chaotic systems, and nonlinear circuit design. She has led over 20 projects, including sub-projects of the National Key R&D Program, National Key Special Projects, National Natural Science Foundation of China (NSFC) General and Youth projects. She has published over 200 journal papers in Nature Communications, IEEE TNNLS, Nano Energy, IEEE TCAS-I, IEEE TVLSI, Materials Horizons, and China Science Information Science. She holds more than 30 authorized national invention patents. Professor Wang is also an associate editor of the renowned international journal Artificial Intelligence Review and has served as a co-chair, program chair, and invited speaker at numerous international conferences.
王丽丹，西南大学人工智能学院教授、博士生导师，重庆英才•创新领军人才，重庆市中青年骨干教师，类脑计算与智能芯片重庆市重点实验室主任。兼任重庆市人工智能学会秘书长，重庆市青年科技领军人才协会理事。主要研究领域为人工智能，包括深度学习、神经形态计算、忆阻器件与芯片、混沌系统与非线性电路设计等，先后承担国家重点研发计划子课题、国家重点专项项目、国家自然科学基金面上项目、国家自然科学基金青年项目等项目20余项，在Nature Communications，IEEE TNNLS，Nano Energy，IEEE TCAS-I，IEEE TVLSI，Materials Horizons和中国科学• 信息科学等发表论文200余篇，授权国家发明专利30余项，担任著名国际期刊Artificial Intelligence Review的副编辑，担任多个国际会议共同主席、程序主席和特邀报告人。
7. Professor Ludovico Minati (University of Electronic Science and Technology of China, Sichuan, China)
Talk Title: Across neurons and silicon: some ideas about the relationship between unusual electronic circuits and neuroscience
Abstract: What makes the brain unique, and what exactly is unique about it from a physical perspective, after all? I will try to approach these questions by first highlighting two aspects. One, the profound differences with respect to present-day computers. Two, how Nature has leveraged, to construct brains, some phenomena that are actually universal, pervasive in other systems, and thus possible to replicate electronically at some level. I will discuss how similar emergent behaviors can be observed across rather diverse systems, and how comparing brain activity to some rather unusual electronic circuits could be inspiring, both for neurophysiology and for electronic engineering. I will briefly overview my recent research attempting to “summarize” in simple electronic circuits, mainly so-called chaotic oscillators, some phenomena arising in other biological and physical scenarios, especially in brain dynamics. Firstly, a gallery of these rather unusual circuits will be walked through, surveying some oscillators based on transistors, gas-discharge tubes, and other electronic components. Secondly, simple networks of these circuits will be considered, demonstrating the spontaneous emergence of phenomena commonly observed in neural recordings, such as community structures, remote interdependences, and so on. Thirdly, some applications will be discussed, comprising the creation of physical instead of simulated in-silico disease models, bio-inspired pattern generation, and engineering applications such as in distributed sensing. While by no means a comprehensive introduction to this young multidisciplinary field, this presentation should hopefully provide some ideas regarding how engineering and neuroscience can provide mutually inspire each other.
Biography: Ludovico Minati received the Ph.D. degree in Neuroscience from the Brighton and Sussex Medical School, Falmer, U.K., in 2012, the D.Sc. (doktor habilitowany) degree in Physics from the Institute of Nuclear Physics, Polish Academy of Sciences, Kraków, Poland, in 2017, and the M.B.A. degree in Technology Management from The Open University, Milton Keynes, U.K., in 2021. Until 2023, he was a Specially Appointed Associate Professor with the Institute of Innovative Research, Tokyo Institute of Technology, Tokyo, and a Freelance Research and Development Consultant. He is now a Professor, Outstanding Young Talent and Director of the Interdisciplinary Nonlinear Dynamics Laboratory at the School of Life Science and Technology, University of Electronic Science and Technology of China, Sichuan, China, and Visiting Professor with the Center for Mind/Brain Sciences, University of Trento, Trento, Italy, He has authored more than 160 articles and several patents. His research interests include nonlinear dynamical systems, chaotic oscillators, reconfigurable analog and digital computing, analog integrated circuits, advanced techniques for biosignal analysis, brain–machine/computer interfaces, and robotics. He is a European Engineer (Eur. Ing.), a Chartered Engineer (CEng) and a member of the Institution of Engineering and Technology, U.K. He is also a member of the Institute of Electronics, Information, and Communication Engineers (IEICE), and the Institute of Electrical Engineers (IEE) of Japan.