In the long river of cybernetics development, Leibniz, Maxwell, Wiener, and Kalman guide the voyage of exploration in cybernetics with their profound theories and exceptional insights, just like four towering lighthouses. Nowadays, Intelligent Networked Things has become a new application field of cybernetics. This field, full of unknowns and opportunities, integrates the informatization and industrialization deeply, and involves many frontier branches, such as big data intelligence, multi-modal intelligence, swarm intelligence, human-machine intelligence, etc., representing the cutting-edge of cybernetics. This keynote speech brings game theory into the research of Intelligent Networked Things, establishes a logical dynamic game model, and proposes new approaches on robust game dynamics. The research results show that evolutionary game theory is not only an effective tool for analyzing swarm intelligence but also a fundamental theory for artificial intelligence. The deep integration of cybernetics and game theory constitutes the key features of the third-generation control theory, and also serves as the core of intelligent networked things.
报告人简介:
王龙,1992年于北京大学获得理学博士学位。1993年在加拿大多伦多大学电子与计算机工程系作博士后(合作导师:B. A. Francis),1995-1997年获德国洪堡基金资助在德国宇航中心机器人研究所进行合作研究(合作导师:J. Ackermann)。现为北京大学教授、博士生导师、长江学者,是“新世纪百千万人才工程”国家级人选、国家杰出青年科学基金获得者。近年来,王龙教授主要从事复杂系统智能控制、机器人动力学与控制、博弈决策与群体智能等方面的研究工作,获得国家自然科学奖(两次)、国家教委霍英东奖(一等奖)、教育部自然科学奖(一等奖)、国家教委科技进步奖(一等奖)、第一届Ho Outstanding Paper Award、第一届关肇直控制理论奖等多项奖励。王龙教授目前担任北京大学系统与控制研究中心主任、北京人工智能学会副理事长、国家出国留学基金评审专家等。目前担任国家自然科学基金委员会信息科学部评审委员、武汉大学、北京航空航天大学兼职教授、美国数学会会员、美国《Mathematical Reviews》评论员、国际自动控制联合会网络系统技术委员会成员、《International Journal of Information and Systems Science》主编(Editor-in-Chief)、《中国科学》、《自然科学进展》、《智能系统学报》、《控制理论与应用》、《控制与决策》、《信息与控制》、《系统仿真学报》、《北京大学学报》、《PLoS ONE》、《IEEE Transactions on Industrial Electronics》、《Journal of Applied Mathematics and Computation》、《Journal of Intelligent and Robotic Systems》、《Journal of Control Theory and Applications》编委、《Springer Journal of Mechanical Science and Technology》机器人与控制领域主编(Editor in Robotics and Control)、中国人工智能学会理事、中国仿真学会常务理事。
Professional Biography:
Prof. WANG Long received his Ph.D. degree in Science from Peking University in 1992. In 1993, he worked as a postdoctoral researcher at the Department of Electrical and Computer Engineering, University of Toronto, under the supervision of Prof. B. A. Francis. From 1995 to 1997, he was funded by the Humboldt Foundation to conduct collaborative research at the Institute of Robotics and Mechatronics, German Aerospace Center (DLR), under the supervision of Prof. J. Ackermann. Currently, WANG Long is a professor and a doctoral advisor at Peking University. He was elected as a Changjiang Scholar, a candidate of the New Century National Hundred, Thousand and Ten Thousand Talent Project, and received the National Science Foundation for Distinguished Young Scholars. In recent years, Prof. WANG Long’s main research interests include intelligent control of complex system, robotic dynamics and control, game decision making and swarm intelligence, etc. He has won National Prize for Natural Sciences twice, Fok Ying-Tong Education Foundation Award from the State Education Commission (the first prize), Natural Science Award of the Ministry of Education (the first prize), Science and Technology Progress Award from the State Education Commission (the first prize), the first Ho Outstanding Paper Award, the first Guan Zhaozhi Award for Control Theory, etc. Prof. WANG Long is the director of Center for Systems and Control, Department of Mechanics and Engineering Science, Peking University, the vice president of Beijing Association for Artificial Intelligence, and an evaluation expert for China Scholarship Council. He is also an evaluation expert for Department of Information Science, National Natural Science Foundation of China, the visiting professor of Wuhan University and Beihang University. He is a member of American Mathematical Society (AMS), a commentator of Mathematical Reviews in America, a member of International Federation of Automatic Control, the Editor-in-Chief of International Journal of Information and Systems Science, a member of Editorial Board for Science China, Progress in Natural Science, CAAI Transactions on Intelligent Systems, Journal of Control Theory and Applications, Journal of Control and Decision, Information and Control, Journal of System Simulation, Journal of Peking University, PLoS ONE, IEEE Transactions on Industrial Electronics, Journal of Applied Mathematics and Computation, Journal of Intelligent and Robotic Systems, and an Editor for Springer Journal of Mechanical Science and Technology. In addition, Prof. WANG Long is a council member of Chinese Association For Artificial Intelligence (CAAI) and an executive council member of Chinese Society of Simulation (CSS).
主旨报告人2杨天若 郑州大学教授报告题目人机物智能:当张量人工智能遇见人机物融合Human-Machine-Thing Intelligence: When Tensor Artificial Intelligence MeetsHuman-Machine-Thing Integration
With the rapid development of Information, Computer, and Communication technologies, human society has become a tightly coupled ternary hybrid space of human, machine, and thing, also known as Cyber-Physical-Social space. One of the ultimate goals of human-machine-thing intelligence research is to provide customized and foresighted services for human being. Therefore, this keynote speech will illustrate the background and related works of human-machine-thing intelligence and demonstrate how the ongoing work in tensor artificial intelligence empowers the development and application of human-machine-thing integration.
Prof. YANG Tianruo is the vice-chancellor of Zhengzhou University. He is a chair professor at the School of Computer Science and Artificial Intelligence, Zhengzhou University and the director of the School of Software Technology. YANG Tianro received his dual Bachelor’s degree in Computer Science and Applied Physics from Tsinghua University, and received his Ph.D. degree of Computer Science from the University of Victoria, Canada. He is a fellow of the Canadian Academy of Engineering (CAE), a fellow of the Engineering Institute of Canada (EIC), a member of the Academia Europaea, and a member of The National Academy of Artificial Intelligence (NAAI), a fellow of IEEE/IET/AAIA. He was selected as a national high-level overseas talent, a Highly Cited Researcher by Clarivate Analytics, one of the Top 2% Scientists Worldwide by Stanford University, a highly ranked scholar with ScholarGPS Ranks of 0.05%, and an ACM distinguished scientist. He is also a chief scientist of the Scientific and Technological Innovation 2030 – ‘New Generation Artificial Intelligence’ Major Project. His main research interest is human-machine-thing intelligence.
主旨报告人3兰旭光 西安交通大学教授报告题目具身智能的挑战与边界:物理世界模型构建与因果推理The Challenges and Boundaries of Embodied Intelligence: The Construction of Physical Model and Its Causal Reasoning
This keynote speech introduces the essence and development of embodied intelligence, especially in the perspective of action intelligence in robots in the physical world, and analyzes the boundaries of embodied intelligence. Then, a self-evolving embodied intelligence architecture is proposed, which incorporates ‘perception-learning-imagination-execution-feedback’ as a key and aims to implement a more efficient and flexible system design of embodied intelligence. Then, a visual common sense reasoning-based method is proposed for the autonomous operation and continuous learning of robots in non-structural scenarios. This method integrates human-machine interaction into multi-modal large language model, enabling robots to perform visual common sense reasoning and autonomous operations in dynamic non-structural scenarios. In addition, this keynote speck also introduces the autonomous collaboration approaches of multi-robots using world model-driven bootstrap model predictive control and imagination-guided large language model for decision, etc. The application of the above approaches in the field of aeronautics, astronautics, logistics, and so on.
Prof. LAN Xuguang is a full professor and a doctoral advisor at Xi’an Jiaotong University. He received the National Science Foundation for Distinguished Young Scholars, China, and is currently a member of the Discipline Evaluation Group of the Academic Degrees Committee of The State Council. His main research interests are computer vision, robotic learning, multi-agent gaming, and human-machine collaboration, etc. He is also a member of the Technical Committee on Coexisting-Cooperative-Cognitive Rbots (Tri-Co Robots) of Chinese Association of Automation (CAA), a council member and the vice-secretary of Chinese Society for Cognitive Science, the vice-director of the Committee on Cognitive System and Information Processing of Chinese Association For Artificial Intelligence (CAAI), and the vice-director of the Committee on Intelligent Unmanned System of Chinese Society of Simulation (CSS). LAN Xuguang has published more than 100 journal and conference papers in the area of artificial intelligence and robotics on IEEE Trans, ICML/ICLR/RSS, etc. He has authorized more than 20 national invention patents and published one book. He hosted more than 10 scientific research projects, including the Key Program of National Natural Science of China, the National Science and Technology Major Project, the Scientific and Technological Innovation 2030 – ‘New Generation Artificial Intelligence’ Major Project, etc. The research results have been applied in the fields of aeronautics and astronautics, etc. Prof. LAN Xuguang was awarded the first prize for Scientific and Technological Progress of CAA and the first prize of National Teaching Achievement. He also serves as a member of the Editorial Board of IEEE Transactions on Neural Network Learning Systems and the chair/program chair of IEEE CYBER2019, ICIRA2021, IEEE RCAR2023, and ICIRA2024. He is currently an IEEE Senior member.
主旨报告人4谢旻 香港城市大学教授报告题目智能系统安全及韧性问题的研究与思考Research and Thinking on Security and Resilience of Intelligent System
Artificial Intelligence has been widely applied across multiple fields, especially in Intelligent Networked Things systems. As the degree of intelligence increases, the issues related to system reliability and security become more and more important. System failure can lead to serious consequences, and even endanger people’s life and property security. System reliability directly impacts its performance and users’ trust. Resilience, as a key indicator of the ability to deal with public emergencies, can be enhanced by incorporating system design optimization and event response plans. This keynote speech will introduce current research and applications related to the security and resilience of intelligent systems, provide researchers and engineers with a deeper understanding of existing boundaries and risks, and help them develop safer and more reliable intelligent systems.
Prof. XIE Min is a chair professor at the City University of Hong Kong. He was admitted to the Early-Entrance-to-College Program at the University of Science and Technology of China in 1978 and was selected to study in Sweden. He received his Doctorate degree from Linkoping University, Sweden in 1987. In 1991, he was awarded the Lee Kuan Yew Research Award of Singapore. He has worked at the National University of Singapore for twenty years. Prof. XIE Min has published several books, including Software Reliability Modelling, Cyber-Physical Distributed Systems, Computing Systems Reliability, etc., and published more than 400 SCI indexed papers. He serves as Editor-in-Chief, Associate Editor, and member of the Editorial Board for many internationally renowned journals. He has trained approximately 80 Ph.D. students, who are currently working in companies or universities in over ten countries. Prof. XIE Min is an IEEE Fellow and a Fellow of the European Academy of Sciences and Arts.
主旨报告人5Weisi Lin(林维斯) 新加坡南洋理工大学教授报告题目Perceptual Modelling for Visual & Multimedia Signals
报告摘要:
As a result of long evolution, humans have developed unique characteristics of perception to sense the outside world with five major sensing organs (for sight, hearing, smell, touch and taste). There are at least two good reasons to make machines we build perceive signals as humans: the goal of AI (at least in its narrower sense) is to mimics human capabilities, such as learning, actions and problem solving; there is an increasing need for harmonious human-machine interaction, since we may have to deal with robots as colleagues, salespersons or care-givers in the near future. The key is to enable perceptual concepts quantitative and computable, because “if you cannot measure it, you cannot improve it” (William Thomson, British Physicist, 1824-1907). In this talk, the major problems and research progress in perceptual signal computing, i.e., to process signals based upon how humans perceive, will be first introduced. The relevant computational models will be then discussed for perceptual signal decomposition, human attention determination, just-noticeable differences (JND), and perceptual signal quality/experience assessment, inclusive of handcrafted and machine–learning based approaches. So far, most research has been performed on visual signals (mainly images and video), with limited work on speech and audio, while more intensive exploration on olfaction, haptics and gustation is expected to emerge. The talk is also to highlight possible application scenarios, based on the presenter’s experience in related academic and industrial projects. The presentation aims to promote further research into R&D opportunities along the direction of AI (including gen AI) in the big data era, intersecting with neuroscience, brain theory, psychophysics, aesthetics, statistics, and user and cultural studies.
主旨报告人6Prof. Makoto Iwasaki 日本名古屋工业大学教授报告题目GA-Based Optimization in Mechatronic Systems: System Identification andController Design
报告摘要:
Fast-response and high-precision motion control is one of indispensable techniques in a wide variety of high performance mechatronic systems including micro and/or nano scale motion, such as data storage devices, machine tools, manufacturing tools for electronics components, and industrial robots, from the standpoints of high productivity, high quality of products, and total cost reduction. In those applications, the required specifications in the motion performance, e.g. response/settling time, trajectory/settling accuracy, etc., should be sufficiently achieved. In addition, the robustness against disturbances and/or uncertainties, the mechanical vibration suppression, and the adaptation capability against variations in mechanisms should be essential properties to be provided in the performance. The keynote speech presents practical optimization techniques based on a genetic algorithm (GA) for mechatronic systems, especially focusing on auto-tuning approaches in system identification and motion controller design. Comparing to conventional manual tuning techniques, the auto-tuning technique can save the time and cost of controller tuning by skilled engineers, can reduce performance deviation among products, and can achieve higher control performance. The technique consists of two main processes: one is an autonomous system identification process, involving in the use of actual motion profiles of system. The other is, on the other hand, an autonomous control gain tuning process in the frequency and time domains, involving in the use of GA, which satisfies the required tuning control specifications, e.g., control performance, execution time, stability, and practical applicability in industries. The proposed technique has been practically evaluated through experiments performed, by giving examples in industrial applications to a galvano scanner in laser drilling manufacturing and an actual six-axis industrial robot.
报告人简介:
Makoto Iwasaki 分别于1986年、1988年和1991年在日本名古屋工业大学(Nagoya Institute of Technology, NIT)获得电气与计算机工程学士、硕士及工学博士学位。现任名古屋工业大学副校长,同时担任该校电气与机械工程系教授。
在IEEE的专业贡献方面,Makoto Iwasaki 积极参与多个学术组织工作,包括2016至2022年担任 IEEE Transactions on Industrial Electronics 联合主编(Co-Editor-in-Chief),以及2018至2021年担任 IEEE 规划与发展副主席(Vice President for Planning and Development)等。他于2015年当选IEEE Fellow,以表彰其在“运动控制器设计中的快速精确定位”方面的杰出贡献。
其当前研究方向主要涉及控制理论在 线性/非线性建模与精密定位中的应用,并通过与工业界的广泛合作研究推动技术创新与实际应用。
主旨报告人7侯宝存 美的集团美云智数研究院院长报告题目智能物联系统赋能企业数字化转型Enterprise Digitalization empowered by Intelligent Networked Things
MideaCloud, as a typical Industrial Internet-of-Things (IIoT) platform, fully absorbs and possesses the ‘Manufacturing Knowledge-Software-Hardware’ innovative advantages of Midea Group and comprehensively integrates the products and services from Midea Group and its ecological partners. This keynote speech introduces the hardware and software integrated, end-to-end, and advanced enterprise digitalization solution applied for the application of MideaCloud in the field of automobile and its accessories, electronic semiconductors, farming and grazing, equipment manufacturing, etc. This solution involves digitalization, lighthouse and digital factory, smart logistics, digital industrial park, industrial clusters, etc. It can empower the digitalization of manufacturing enterprises of all sizes, driving the development of the digital economy in various industries and regions. MideaCloud has been selected as a National IIoT platform for three years for various industries and various fields.
Dr. HOU Baocun is the president of Midea Cloud Technology Research Institute, the director of Industrial Cloud Manufacturing Innovation Center in Guangdong Province, the director of the Research Center of Intelligent Manufacturing Software Engineering Technology in Guangdong Province, a committee member of the State Key Laboratory of Intelligent Manufacturing Systems Technology, the Head of the Industry-University-Research Cooperation and Application Group of Artificial Intelligence Industry Alliance (AIIA), the vice-chair of the Platform Group of Alliance of Industrial Internet (AII), and the vice-president of National Industrial Internet Industry-Education Integration Community. He was selected for the Guangdong Pearl River Talent Program, and recognized as a leading talent and high-level industrial talent in Foshan, Guangdong. He has been engaged in research, product development, and application implementation in the areas of enterprise digitization, IIoT, industrial software, intelligent manufacturing/cloud manufacturing, complex system modeling, and simulation, etc. HOU Baocun is a co-inventor of Cloud Manufacturing. He hosted more than 10 IIoT-related projects from the Ministry of Science and Technology of China and the Ministry of Industry and Information Technology of China. He has been awarded 3 second prizes of Provincial and Ministerial-level Science and Technology Progress Awards, authorized more than 20 national invention patents, published approximately 100 papers, and co-authored 3 books.
主旨报告人8刘洪海 哈尔滨工业大学(深圳)医工学院教授报告题目体联网感知与增强Perception and Enhancement in Body Internet
In response to the current situation of social aging and low birth rate, this keynote speech introduces the bottleneck of diagnosis and treatment technologies and demonstrates the necessity of human behavioral function quantification and control. Then, a human-centered in-body behavioral quantification network, termed ‘Body Internet’, will be introduced along with its core sub-systems, including wearable sensors and medical information analysis, etc. Then, using stroke and autism as case studies, this keynote speech elaborates on the diagnostic methods for function quantification of motor behaviors and discusses their technological transformation in hospital clinical trials and practices.
Prof. LIU Honghai is a full professor and the director of the School of Medical Engineering, Harbin Institute of Technology (Shenzhen). He is a member of the Academia Europaea and IEEE/IET Fellow. His main research interests are human-machine interaction, embodied intelligence, and the theories and applications of medical-machine-assisted system for brain diseases. He has hosted the National Key Research and Development Program, the Key Program of National Natural Science of China, etc. The research results have been successfully applied to multi-degree of freedom (multi-DOF) dexterous artificial limb, early diagnosis and treatment of autism, and precise diagnosis and treatment of stroke, etc. He has published more than 400 journal and conference papers. Currently, he serves as the Editor-in-Chief of IEEE Trans. Industrial Informatics and a member of the Editorial Board of IEEE Trans. Cybernetics.