Prof. Xiao He, Tsinghua University, China

Biography: Xiao He is a tenured professor at the Department of Automation, Tsinghua University, Director of the Centre for Safety Control Technology Research, and Head of the Key Area Innovation Team under the Ministry of Transport. His research interests include state estimation, fault diagnosis, fault-tolerant control, and real-time safety assessment of dynamic systems. He has published over 300 papers in domestic and international journals and conferences. He has led National Natural Science Foundation projects including Young Scientist Fund A, Young Scientist Fund B, and Key Projects. In 2021, he received the Young Scientist Award from the Chinese Association for Automation. He is currently the deputy secretary-general of Chinese Association of Automation (CAA), deputy director and secretary-general of the fault diagnosis committee of the CAA, deputy director of the process control committee of the CAA, deputy director of the intelligent control and systems committee of the Chinese Institute of Command and Control. He serves as an editorial board member for several international journals, including IEEE TNNLS, IEEE TASE and Control Engineering Practice. He has received the First Prize of the Jilin Province Science and Technology Progress Award in 2018, the First Prize of the CAA Natural Science Award in 2015 and 2020, the First Prize of the CAA Technical Invention Award in 2022, and the Second Prize of the Beijing Natural Science Award in 2023. Four doctoral students he has supervised (including co-supervised) have won the Outstanding Doctoral Dissertation Award of the CAA in 2018, 2021, 2022, and 2024.

Speech Title: Physical Safety Enhancement Technologies for Embodied Intelligent Systems

Abstract: Embodied intelligent systems are typical complex dynamic systems that face significant challenges, including multi-subsystem coupling, multiple perception-decision closed loops, strong nonlinearity and uncertainty, and interaction with open environments. To address these issues, a real-time safety enhancement technical framework tailored for embodied intelligent systems has been established. This framework covers key aspects such as dynamic system state estimation, fault diagnosis, fault-tolerant control, and safety assessment. Specifically, a novel networked strong tracking nonlinear state estimation method is proposed; an active diagnosis theory based on auxiliary signal excitation is developed; and the underlying mechanisms of how faults, component performance, and system structure affect consistency and safety margins are revealed. Furthermore, from the perspectives of efficient data value utilization and online updating of assessment models, a novel real-time safety assessment method for dynamic systems is introduced. The proposed approaches have significantly enhanced the operational safety of embodied intelligent systems.

Prof. Guanghui Wen, Southeast University, China

Biography: Guanghui Wen received the Ph.D. degree in mechanical systems and control from Peking University, Beijing, China, in 2012.Currently, he is an Endowed Chair Professor and Vice Dean with the School of Automation, Southeast University, Nanjing, China. His current research interests include autonomous intelligent systems, complex networked systems, distributed control and optimization, resilient control, and distributed reinforcement learning. Prof. Wen was the recipient of the National Science Fund for Distinguished Young Scholars, the China Youth Science and Technology Award, the Australian Research Council Discovery Early Career Researcher Award, and the Asia Pacific Neural Network Society Young Researcher Award. He currently serves as a Technical Editor of the IEEE/ASME Transactions on Mechatronics and an Associate Editor of the IEEE Transactions on Control of Network Systems, the IEEE Transactions on Industrial Informatics, the IEEE Transactions on Neural Networks and Learning Systems, the IEEE Transactions on Intelligent Vehicles, the IEEE Transactions on Fuzzy Systems, the IEEE Transactions on Systems, Man and Cybernetics: Systems, the IEEE Open Journal of the Industrial Electronics Society, and the Asian Journal of Control. Prof. Wen has been named a Highly Cited Researcher by Clarivate Analytics since 2018. He is an IET Fellow.

Speech Title: Distributed Consensus and Optimization of Multi-Agent Systems with Switching Communication Topologies

Abstract: In recent years, the development of perception, communication, and embedded technologies has had a transformative impact on system analysis and control methods. Modern engineering control systems are increasingly characterized by networked structures and intelligent units. Within this context, the concept of multi-agent systems (MASs) has emerged, and the distributed cooperative control and optimization of such systems have gradually become a research frontier in the fields of systems and control. In practice, due to factors such as the limited communication range of agents and interference in communication links, the communication topology of MASs often exhibits dynamic switching characteristics. This talk begins by discussing the key issues of consensus control in MASs under switching communication topologies, outlining the critical techniques for addressing these problems: the common Lyapunov function method and the multiple Lyapunov function method. For MASs with directed switching communication topologies, it presents the construction methods and consensus criteria of multiple Lyapunov functions based on nonsingular M-matrix theory, and further explores low-conservatism multiple Lyapunov function construction methods based on Lyapunov inequalities and optimization techniques. On this basis, the robust optimization problems of MASs with physical dynamics under switching communication topologies are discussed. Finally, the application of the related theoretical results in the formation control of unmanned surface vessels is shared, along with personal insights on related emerging research topics.

Prof. Jiahu Qin, University of Science and Technology of China, China

Biography: 秦家虎，中国科学技术大学讲席教授、博导，主要研究兴趣为自主智能系统协同、优化与决策。在相关领域发表录用Springer英文专著两部，Automatica 及 IEEE Trans. 汇刊论文100余篇；授权中国发明专利60余件。主持国家杰出青年基金、优秀青年基金、重点项目、首批教育部学科突破先导项目课题、科技创新2030—“新一代人工智能”重大项目课题等国家级项目10余项。获中国自动化学会自然科学奖一等奖 (排名1)、中国自动化学会技术发明奖一等奖 (排名1)、黑龙江省自然科学一等奖 (排名3)、中国自动化学会“青年科学家奖”、中国控制会议“关肇直奖”、IEEE工业电子学会最佳会议论文奖。目前担任中国自动化学会副秘书长、安徽省机器人学会副理事长、中国自动化学会“青年工作委员会”副主任委员以及Automatica、IEEE/ASME TMECH、IEEE TIE、IEEE TCNS、《自动化学报》等期刊编委。

Speech Title: Robot Autonomy in Complex Environments: Navigation and Mobile Manipulation

Abstract: This talk presents the recent research progress of our group in autonomous robot perception, planning, and control, as well as the application of these research outcomes to scenarios such as autonomous drone racing and mobile manipulation with legged robots.