Speakers
Keynote Speakers
Prof. Jun Wang
IEEE Fellow, IAPR Fellow
City University of Hong Kong, China
Speech Title: AI-Powered Planning and Control of Chiller Systems
Abstract: Heating, ventilation, and air conditioning (HVAC) systems consume about 40% of the energy in commercial and residential buildings. As a crucial part of heat removal from a thermal space to the outside, a chiller system accounts for more than half of the energy consumption in an HVAC system. In this talk, I will first describe the problem formulations for chiller loading with cardinality constraints as well as physical constraints. I will then present several collaborative neurodynamic systems to solve the formulated constrained optimization problems for chiller loading in centralized and distributed settings. In addition, I will propose neurodynamics-driven approaches to receding-horizon distributed chiller loading and the hybrid model predictive control of distributed chiller systems.
Bio: Jun Wang is a chair professor at City University of Hong Kong and a school dean in 2023/2024 academic year. Prior to this position, he held various academic positions at Dalian University of Technology, Case Western Reserve University, University of North Dakota, and the Chinese University of Hong Kong. He also held various short-term visiting positions at USAF Armstrong Laboratory, RIKEN Brain Science Institute, Shanghai Jiao Tong University, Dalian University of Technology, and Swinburne University of Technology. He received a B.S. degree in electrical engineering and an M.S. degree from Dalian University of Technology and his Ph.D. degree from Case Western Reserve University. He was the Editor-in-Chief of the IEEE Transactions on Cybernetics in 2014-2019 and is currently the Editor-in-Chief-Elect of the IEEE Transactions on Artificial Intelligence. He is an IEEE Life Fellow, IAPR Fellow, and a foreign member of Academia Europaea. He is a recipient of the APNNA Outstanding Achievement Award, IEEE CIS Neural Networks Pioneer Award, CAAI Wu Wenjun AI Achievement Award, and IEEE SMCS Norbert Wiener Award, among other distinctions.
Prof. Fuchun Sun
IEEE Fellow
Tsinghua University, China
Speech Title: Morphological intelligence and multi-agent general behavior game evolution
Abstract: This report first reviews the development of embodied intelligence, and focuses on the main progress of morphological intelligence research. Then, the general behavior evolution of multi-agent is discussed in depth, and a framework based on hierarchical equivariant graph neural network is proposed, so that multi-agent can effectively adapt to different forms and tasks, and realize the game and evolution of behavior strategies. At the same time, using geometric symmetry, the behavior strategy has geometric invariance and can be generalized in the whole three-dimensional space, thus significantly improving the learning efficiency and versatility of the embodied intelligent system in a complex environment. Finally, the report discusses the potential development direction of embodied intelligence and multi-agent systems in the future intelligent environment.
Bio: Fuchun Sun, Professor, Department of Computer Science and Technology, Tsinghua University, Doctoral Supervisor, IEEE / CAAI / CAA Fellow, National Distinguished Young Scholars Fund Winner ; he is also a member of the Academic Committee of Tsinghua University, the Deputy Director of the Professor Committee of the Department of Computer Science and Technology, and the Director of the Intelligent Robot Center of the Institute of Artificial Intelligence of Tsinghua University. He is also a member of the overall expert group of the national key research and development plan robot, the vice chairman of the China Artificial Intelligence Society, the supervisor of the China Automation Society and the executive director of the China Cognitive Science Society. He is also editor-in-chief of the international journal ' Cognitive Computation and Systems ', ' AI and Autonomous Systems ', executive editor of ' CAAI Artificial Intelligence ', and deputy editor-in-chief of the international journal ' IEEE Trans.on Fuzzy Systems '. Editor of ' Robots and Autonomous Systems ' and ' International Journal of Social Robots '.
Prof. Panfeng Huang
Dean of School of Astronautics NPU,
Northwestern Polytechnical University, China
Speech Title: Progress and Prospects of Robot Teleoperation Technology for On-Orbit Services
Abstract: Space is the fourth living space for humanity and also the high ground of international strategic competition. The demand for on orbit services such as space attack and defense, orbital debris removal, and on orbit maintenance is becoming increasingly strong. For complex, dynamic operation scenarios and non-cooperative targets, the autonomous intelligence of space robots is insufficient, and it is necessary to use teleoperation technology to achieve efficient on orbit services for space robots. This report will introduce the scientific issues, key technologies, research progress, and application prospects of human-machine hybrid intelligence in the field of on orbit collaborative teleoperation, based on the research foundation of our research group in the field of collaborative teleoperation between heaven and earth. Under current conditions, intelligent teleoperation between heaven and earth provides an effective solution to the technological bottleneck in the field of space on orbit services, which will greatly enhance the operational capabilities of space robots in teleoperation between heaven and earth and other remote control fields.
Bio: Huang Panfeng, Dean, Professor, Doctoral Supervisor of the School of Astronautics at Northwestern Polytechnical University, recipient of the National Outstanding Youth Fund of NSFC, leading talent in scientific and technological innovation under the National "Ten Thousand Talents Plan", recipient of the National Defense Science and Technology Excellence Youth Fund, Chief Scientist of the National Key R&D Program, currently serving as a member of the 8th Control Science and Engineering Discipline Evaluation Group of the Academic Degrees Committee of the State Council, Deputy Leader of a Military Expert Group, Expert of the Ministry of Science and Technology's Science and Technology Innovation 2030- New Generation Artificial Intelligence Major Project Management Expert Group, and invited expert of the Manned Space Application and Service Expert Group. He also formerly served as an expert in the National 863 Program Major Project Expert Group and Deputy Chief Engineer of National Major Project. His main research directions include space robot technology, teleoperation technology, intelligent control of spacecraft, human-machine hybrid intelligent control, cluster collaborative control, etc. He published more than 150 SCI papers and won multiple scientific and technological awards such as the first prize of Shaanxi Province in Natural Science, the first prize of Military Science and Technology Progress, and the second prize of National Defense Technology Development; And served as an editorial board member for IEEE Transactions on Neural Networks and Learning Systems, Robotica, ACTA AUTOMATICA SINICA, Journal of Astronautics, Journal of Aeronautics (Chinese and English versions), Control Theory and Applications, Robot, Journal of Systems Engineering and Electronic Technology, Journal of National University of Defense Technology, and other journals.
Prof. Junwei Han
IEEE Fellow, IAPR Fellow
Northwestern Polytechnical University, China
Speech Title: Visual Perception of Unmanned Systems : Challenges, Countermeasures and Prospects
Abstract: Visual perception of unmanned system is a key technology of integrated space-air-ground-sea observation system. Compared with natural images, the images observed by unmanned systems have the characteristics of variable target directions, complex target types and quantities, scarce samples in specific fields, and single imaging perspective. In addition, different platforms, different lighting, weather conditions, and atmospheric parameters will have an impact on image acquisition. These comprehensive factors make the visual perception task of unmanned systems face greater challenges and more difficult problems than natural image understanding. What kind of sparks will be generated when AI is deeply integrated with the visual perception of unmanned systems ? This report first summarizes and analyzes the challenges faced by target detection and recognition tasks in unmanned systems. Then it focuses on the research progress and typical applications of our team in the direction of rotation invariant target detection, directed target detection, weakly supervised target detection, small sample target detection, and target model recognition. Finally, the future research work is prospected.
Bio: Han Junwei, Dean of School of Automation, Northwestern Polytechnical University, IEEE Fellow, Special Professor of Yangtze River Scholars in 2018, Leading Talent in Scientific and Technological Innovation of the National Ten Thousand Talents Program, and ' Highly Cited Scientist ' of Coreview Safety Ball. The main research directions are artificial intelligence, pattern recognition, brain-like computing, remote sensing image processing, etc. More than 150 academic papers have been published in top journals / conferences such as Proceedings of the IEEE, IEEE TPAMI, CVPR, MICCAI, etc., and the papers have been cited nearly 40,000 times. Three papers were selected as the top 100 most influential international academic papers in China. It was nominated for the most influential paper award of the IEEE Society for Earth Sciences and Remote Sensing in 2021 and 2023, the best paper award of the international journal IEEE TCSVT 2021, the best paper award of the international conference IEEE BIBM 2018, and the best student paper award of the international conference ACM Multimedia 2010, MICCAI 2011 and ICME 2016. Training a number of doctoral students / post-doctors to obtain excellent doctoral dissertations of the Chinese Society of Image and Graphics, excellent doctoral dissertations of Shaanxi Province, post-doctoral innovative talent support program, training a number of doctoral students / post-doctors to obtain excellent doctoral dissertations of the Chinese Society of Image and Graphics, excellent doctoral dissertations of Shaanxi Province, post-doctoral innovative talent support program, national youth talent program, highly cited scientists, etc. It won the first prize of science and technology in Shaanxi Province, Wu Wenjun 's first prize of artificial intelligence technology invention and other 9 provincial and ministerial science and technology awards. He served as an editorial board member of several domestic and foreign journals such as IEEE TPAMI, ' Science in China : Information Science ', and chaired international conferences such as CVPR.
Prof. Badong Chen
IEEE Senior Member
Xi'an Jiaotong University, China
Speech Title: Information Theoretic Learning for brain inspired computing, brain computer interfaces and brain disease diagnosis
Abstract: Information theory has been widely applied in the field of machine learning and has attracted increasing attention from scholars. Researchers have proposed various information theoretic learning methods for different learning problems, such as the minimum error entropy (MEE) criterion in supervised learning and the information bottleneck (IB) principle in representation learning. This talk introduces the basic concepts of Information Theoretic Learning (ITL), elaborates on new learning paradigms and methods, and explores the applications of ITL in brain inspired computing, brain computer interfaces, and brain disease diagnosis.
Bio: Badong Chen is a professor at the Institute of Artificial Intelligence and Robotics, Xi 'an Jiaotong University and a Yangtze River scholar of the Ministry of Education. In 2008, he graduated from Tsinghua University with a doctorate in computer science. The research fields include machine learning, artificial intelligence, brain-computer interface, and robotics. He has published more than 300 academic papers in internationally renowned journals and conferences, and the papers have been cited more than 15,000 times. More than 30 national invention patents were authorized and 6 academic monographs were published. He was included in the list of top 2 % scientists in the world and Elsevier 's list of China 's highly cited scholars. It won the first prize of natural science of the Ministry of Education, the first prize of natural science of the Chinese Society of Automation, and the young scientist award of the Chinese Society of Automation. He is the director of Chinese Cognitive Science Association and the editorial board member of IEEE TNNLS / TCDS / TCSVT. He presided over the key projects of the National Natural Science Foundation of China, the key support projects of the National Natural Science Foundation of China, the key projects of the joint fund, the 973 plan project, the national key research and development plan project and other scientific research projects.
Prof. Jin Xu
Peking University, China
Speech Title: From Biological Computing to Probe Machine
Abstract: Whether in theory or in application, a major problem currently facing is that electronic computers cannot effectively solve the so-called " combinatorial explosion " problem, which is characterized by an exponential increase in the amount of calculation required as the scale of the problem increases. Such problems are NP-complete, such as resource allocation, scheduling, password deciphering, etc. Fortunately, all NP-complete problems are equivalent, which means that we only need to study a class of NP-complete problems. This report focuses on the typical NP-complete problem of graph coloring, from the exploration of computational models to the development of special machines. In terms of computational models, we introduce the work of biological computing experiments with a search scale of 359, and the team is conducting experiments with a search scale of 3100. In particular, a fully parallel computing model-probe machine found in the process of biological computing research is introduced. Different from the traditional data processing method, the probe machine data is a new type of calculation model that is freely arranged in space and can directly process information between any two data. This new data design and operation method is abstracted from the probe hybridization technology in DNA molecular operation, so it is called probe machine. In the research and development of special machine, the computer model of graph coloring probe based on biological and electronic technology is introduced, It includes DNA-I probe computer, II-probe computer and electronic probe computer based on FPGA.
Bio:Xu Jin, professor of Peking University, doctoral supervisor. Doctor of science and engineering. Mainly engaged in theoretical computer and algorithm research. He has published 5 academic monographs, 1 translation and more than 300 academic papers. As the first complete person, he won 1 second-class national natural science award, 2 first-class natural science awards from the Ministry of Education, and 1 first-class natural science award from Hubei Province. It has presided over the National Natural Science Foundation of China, major international cooperation, special funds, major instrument projects, 863 projects, national major projects, and national key research and development plans. He is currently the Deputy Chairman of the Circuits and Systems Branch of the China Electronics Society, the Deputy Chairman of the Cloud Computing and Big Data Committee of the China Communications Society, the Director of the China Cyberspace Security Association, and the Chairman of the Biocomputing and Bioprocessing Professional Committee of the Circuits and Systems Branch. Associate editor of ' Artificial Intelligence Review ' and ' Journal of Electronics and Informatics ', Editor of ' Journal of Electronics ', ' Journal of Computer ' and ' Journal of Software ' ; he has served as a field expert of the Science and Technology Committee of the Military Commission, the Chairman of the Special Committee on Graph Theory and System Optimization of the Electronic Society, the Chairman of the Hubei Provincial Operational Research Association, the Deputy Chairman of the Beijing Municipal Operational Research Association, and the Member of the Cyberspace Security Education and Advisory Committee of the Ministry of Education ;
Prof. Rubin wang
East China University of Science and Technology, China
Speech Title: Neural Information Processing Follows the Working Principle of Brain
Abstract: The content of this report mainly includes : ( 1 ) the research status of brain science ; ( 2 ) What kind of theory is the potential way to solve the problem ; ( 3 ) Why to propose a new W-Z neuron model ; ( 4 ) Introduction of research results of large-scale neuroscience model ; ( 5 ) Challenges faced by brain science and Artif.Intell.Rev. ' s evaluation of brain theory. Through the above introduction, the core scientific problems that have not been solved so far in neuroscience and the potential frontier brain theories and important methodologies for solving these major scientific problems are expounded. This paper explains the different levels of original innovation in brain theory, the criteria for judging original innovation topics, and puts forward new insights into what is a brain-like model from the perspective of brain-like computing. The basic concepts of large-scale neuroscience and global brain models are given.
Bio: Rubin Wang, director and second-grade professor, Institute of Cognitive Neurodynamics, East China University of Science and Technology, Hangzhou University of Electronic Science and Technology hired lecture professor. SCI source journal Cognitive Neurodynamics chief editor, JCR Neuroscience Zone 2. Mainly engaged in neurodynamics and brain theory research. Ten projects supported by the National Natural Science Foundation of China include one key project and seven general projects. He has published more than 200 research papers in international journals. He was emeritus professor and research professor at Osaka University and Tamagawa University.