Keynote Speech

主旨报告人1 王龙 北京大学教授 报告题目 从莱麦维卡到智能物联 From Leibniz, Maxwell, Wiener, and Kalman to Intelligent Networked Things
报告摘要：
  在控制科学发展的漫漫长河中，莱布尼兹、麦克斯韦、维纳、卡尔曼犹如四座巍峨耸立的灯塔，以其深邃的理论与卓越的洞见，为控制科学的探索航程指引着方向。如今，智能物联（Intelligent Networked Things）成为控制科学开拓的全新疆域。这片充满未知与机遇的海域，汇聚了“两化一融合”理念，以及大数据智能、跨模态智能、群体智能、人机混合智能、自主智能系统等多个前沿“岛屿”，代表着控制科学发展的最前沿。本报告将博弈论引入智能物联系统研究中，构建逻辑动态博弈模型，并提出鲁棒博弈动力学的新方法。研究成果显示，演化博弈理论不仅是剖析群体智能的有效利器，更是人工智能的重要基础理论；控制论与博弈论的深度融合，则构成了第三代控制理论的核心特征，同时也是智能物联系统研究的关键所在。
Report Abstract:
  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 Meets Human-Machine-Thing Integration
报告摘要：
  随着信息技术、计算机技术和通信技术的迅猛发展，人类社会逐渐成为一个人、机、物紧密耦合的三元混合空间，也称之为信息-物理-社会空间。如何在这个混合空间中为人类提供个性化、前瞻性的服务，人机物智能研究的终极目标之一。为此，本报告重点讲述了它的背景、现状以及我们一直从事的张量人工智能如何赋能人机物融合的研究和应用。
Report Abstract:
  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.
报告人简介：
  杨天若, 郑州大学学术副校长，学科首席教授，计算机与人工智能学院、软件学院院长。毕业于清华计算机系, 获计算机和应用物理双学士，加拿大维多利亚大学获计算机科学博士学位。加拿大工程院院士，加拿大工程研究院院士，欧洲科学院院士，美国国家人工智能科学院院士, IEEE/IET/AAIA 会士，国家海外高层次人才入选者, 科睿唯安全球高被引科学家, 斯坦福全球前 2%科学家, ScholarGPS全球前0.05%顶尖学者，ACM 杰出科学家，国家科技创新2030新一代人工智能重大项目首席科学家。主要从事人-机-物智能研究。
Professional Biography:
  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
报告摘要：
  报告简要介绍具身智能的内涵和发展现状，特别是机器人在物理世界行为智能方面的进展和面临的挑战，并分析了具身智能的边界。进一步提出了一种自我进化的具身智能框架，该框架以“感知-学习-想象-执行-反馈”一体化为核心理念，旨在实现更高效、更灵活的具身智能系统设计。构建了非结构场景基于视觉常识推理的机器人自主作业和持续学习方法，将多模态大模型融入人-机器人交互，使得机器人能够在动态非结构场景进行视觉常识推理，完成自主作业。报告还介绍了世界模型驱动的自举模型预测控制、想象引导决策大模型的多机器人自主协同方法，以及相关算法在航天、航空、物流等领域的应用。
Report Abstract:
  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.
报告人简介：
  兰旭光，教授，博士生导师，国家杰出青年科学基金获得者，国务院学位委员会学科评议组成员。现任西安交通大学人工智能学院教授，研究领域为计算机视觉、机器人学习、多智能体博弈及人机共融协作等。担任中国自动化学会共融机器人专委会主任委员，中国认知科学学会理事、副秘书长，人工智能学会“认知系统与信息处理”专委会副主任委员，仿真学会“智能无人系统建模仿真”专委会副主任委员。在人工智能与机器人领域的著名期刊和会议上如IEEE Trans和ICML/ICLR/RSS等发表论文100余篇，获得国家发明专利授权20余项，出版编著1部。主持国家自然科学基金重点、国家科技重大专项、科技创新2030人工智能重大项目等科研项目10余项，相关研究成果已应用于航空、航天等领域，获自动化学会科技进步一等奖和国家教学成果一等奖。担任国际期刊IEEE Transactions on Neural Network Learning System等期刊的编委。曾担任IEEE CYBER2019 和ICIRA2021大会联合程序主席，IEEE RCAR2023和ICIRA2024大会主席，IEEE 高级会员。
Professional Biography:
  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
报告摘要：
  人工智能在多个领域得到了广泛应用，特别是智能物联系统。随着智能化程度的提升，系统的可靠性相关问题，包括系统安全问题，变得愈发重要。系统故障可能导致严重后果，甚至危及人们的生命和财产安全。系统的可靠性直接影响其性能和用户信任，而韧性作为应对突发事件能力的关键指标，可以通过优化设计和事件响应计划来增强系统的抗压能力。这里我们介绍一些相关的研究，大家共同关注智能系统的安全及韧性的研究与应用，更深入地理解这些系统的局限性与风险，以便开发出更安全、可靠的智能系统。
Report Abstract:
  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.
报告人简介：
  谢旻教授现任香港城市大学讲座教授，曾在1978年以全国第一名的成绩考入中国科学技术大学少年班，次年选派瑞典留学，1987年博士毕业于瑞典Linkoping University，1991年获得新加坡李光耀研究奖，在新加坡国立大学任教二十年。谢教授出版了多本可靠性相关的专著、包括 Software Reliability Modelling, Cyber-Physical Distributed Systems, Computing Systems Reliability等，发表了400余篇SCI期刊论文，在诸多国际知名杂志担任或曾经担任主编、副主编或编委。谢教授培养的近80名博士毕业生，目前在全球十多个国家的企业或高校工作。谢教授2005年入选IEEE Fellow，2022年当选欧洲科学与艺术院院士。
Professional Biography:
  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5 Weisi 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.
报告人简介：
  Weisi Weisi Lin（林维斯）教授：伦敦大学国王学院博士，新加坡南洋理工大学计算机科学与工程学院教授、项目主任，新加坡工程技术学院的荣誉院士，IEEE会士和IET会士。主要从事图像处理、主观视觉模型、视频压缩、多媒体传输、计算机视觉以及嵌入式系统等方面的研究。发表了150篇国际期刊论文，220余篇国际会议文章，主编并参与多部著作编写。在20多个国际会议上被邀请作为主讲人发表学术演讲。任IEEE TIP、IEEE TCSVT等多个IEEE顶级汇刊副主编。
主旨报告人6 Prof. 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 and Controller 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
报告摘要：
  美擎工业互联网平台作为典型的智能物联系统，充分吸收并具备美的集团“制造业知识、软件、硬件”三位一体的创新优势，全面整合美的集团和生态伙伴的产品和服务能力，在汽车汽配、电子半导体、农牧食品、装备制造等垂直行业形成了软硬一体、端到端、领先的数字化解决方案，涵盖数字化转型、灯塔和数字工厂、智慧供应链、数字园区、产业集群等领域，赋能大中小各类制造企业数字化转型，带动行业/区域数字经济发展，已连续三年入选国家级跨行业跨领域工业互联网平台。
Report Abstract:
  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.
报告人简介：
  侯宝存，博士，研究员，美的集团美云智数研究院院长，广东省工业云制造创新中心主任，广东省智能制造软件工程技术研究中心主任，复杂产品智能制造系统技术全国重点实验室专委会委员，中国人工智能产业发展联盟产学研融合与应用组组长，中国工业互联网产业联盟平台组副主席，全国工业互联网行业产教融合共同体副理事长。入选广东省“珠江人才计划”，佛山市领军人才、高层次产业人才。长期从事企业数字化、工业互联网平台、工业软件、智能制造/云制造、复杂系统建模仿真等技术研究、产品研发和应用实施工作。“云制造”理念参与提出者与实践团队核心成员，主持完成国家科技部、工信部10多项智能制造和工业互联网相关项目，获得省部级科技进步二等奖3项，授权发明专利20余项，在学术刊物、国内外会议上发表高水平论文近百篇，合作出版著作3部。
Professional Biography:
  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
报告摘要：
  针对目前社会老龄化和少子化等问题，通过诊疗现状与技术瓶颈说明人体行为功能量化和调控的必要性；提出以人为中心的在体行为量化网络“体联网”及其可穿戴传感器、医疗信息分析等核心子系统，并以脑卒中和孤独症精准诊疗为例，阐述运动行为功能量化的诊疗方法及其技术转化在医院临床验证与示范推广。
Report Abstract:
  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.
报告人简介：
  刘洪海，哈尔滨工业大学（深圳）医工学院教授院长、欧洲科学院院士(MAE)和IEEE/IET Fellow。长期从事人机交互、具身智能和脑疾病医疗机器辅助系统理论及应用，主持国家重点研发计划、国自然基金重点等项目，研究成果已在多自由度灵巧假肢、自闭症早期诊疗和脑卒中精准诊疗等领域得到成功应用。已发表 400 多篇国际权威杂志和会议论文，现担任《IEEE Trans. Industrial Informatics》共同主编、《IEEE Trans. Cybernetics》等期刊编委。
Professional Biography:
  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.

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