Speakers

Prof. Loi Lei Lai

Guangdong University Of Technology, China

IEEE Life Fellow, IET Fellow

Professor Loi Lei Lai (赖来利) received the B.Sc. (First Class Hons.) and Ph.D. from the University of Aston, Birmingham, UK in 1980 and 1984 respectively. His D.Sc. is from City, University of London, London, UK, in 2005. All degrees are in electrical and electronic engineering. Professor Lai is currently Chairman of DRPT International Incorporated, Australia. He was a Pao Yue Kong Chair Professor with Zhejiang University, Hangzhou, China; Professor & Chair of Electrical Engineering with City, University of London, UK and a University Distinguished Professor with Guangdong University of Technology, Guangzhou, China. Professor Lai received an IEEE Third Millennium Medal, the IEEE Power and Energy Society (IEEE/PES) UKRI Power Chapter Outstanding Engineer Award in 2000, a special award from City, University of London in 2005 and is its honorary graduate, the IEEE/PES Energy Development and Power Generation Committee Prize Paper in 2006 and 2009, the IEEE Systems, Man, and Cybernetics Society (IEEE/SMCS) Outstanding Contribution Award in 2013 and 2014, the Most Active Technical Committee Award in 2016, and his research team has received a Best Paper Award in the IEEE International Smart Cities Conference in October 2020. Professor Lai is an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, Editor in-Chief of the IEEE Smart Cities Newsletter; a member of the IEEE Smart Cities Board of Governor; Member-at-large, IEEE Technical Activities Board (TAB) Committee on Standards & Chair of the Seed Funding ad hoc Committee, and the Chair of IEEE/SMCS Standards Committee. He was a member of the IEEE Smart Grid Steering Committee; the Director of Research and Development Center, State Grid Energy Research Institute, China; a Vice President for Membership and Student Activities of IEEE/SMCS; and a Fellow Committee Evaluator and Distinguished Lecturer for the IEEE Industrial Electronics Society. His current research and development interests are in smart cities, smart grid, clean energy and computational intelligence. He is an IEEE Life Fellow and IET Fellow.

Prof. Zhijun Zhang

South China University of Technology, China

IEEE CIS (Computational Intelligence) Guangzhou Chapter, IEEE Senior Member

Zhang Zhijun, a professor of South China University of Technology, doctoral advisor. Prof. Zhang is National top young talents, IEEE CIS (Computational Intelligence) Chairman of Guangzhou Chapter and IEEE Senior member. The director of the bionic intelligent robot laboratory of South China University of Technology, the director of the Hongqian Intelligent Human Machine Interaction Joint Laboratory of South China University of Technology, the director of the Tianxia Valley Artificial Intelligence and Digital Agriculture Joint Laboratory of South China University of Technology, the high-level talent scholar of South China University of Technology, the outstanding youth of Guangdong Province, and the top young talents of Guangdong Province in scientific and technological innovation. He has been engaged in neural network, machine learning, big data analysis, control optimization, swarm unmanned system and robot research for a long time. He is a member of the Mixed Intelligence Committee of the Chinese Society of Automation, a member of the Joint Integration Robot Committee, a member of the Adaptive Dynamic Planning and Intensive Learning Committee, a member of the Visual Perception and Computing Committee of the Chinese Society of Graphics and Images, an editorial board member of the SCI journal Electronics, an executive editor in chief of the Global Journal of Neural Science, an associate editor in chief of the International Journal of Robotics and Control, and a reviewer of more than 20 international SCI professional journals, Evaluator of China National Foundation Committee and Guangdong Provincial High tech Enterprise. It is the first variable parameter dynamic learning neural network in the world, and the error convergence law has reached the super exponential level, which is the first time that the quantification can be proved to reach this level in the field of time varying system problem solving; It is also the first network model to achieve the effect of suppressing large noise and strong interference to zero in a finite time. It is used for prediction, recognition, control, optimization and other scenarios. It is the first time to put forward the concept of flight redundant robot internationally, design and develop a prototype, and create a neural controller for flight robots. A real-time natural human-computer interaction method based on neurodynamics is proposed to solve the problem of real-time natural human-computer interaction of robots. The security price prediction model and method based on morphology and the depth dynamic learning detection strategy based on medical images are proposed. We independently developed mobile inspection robots, nurse robots, multimodal polar human emotion interactive intelligent robots, intelligent flying robots, multimodal rehabilitation wheelchair assisted robots, intelligent robots for detecting anti epidemic masks in complex environments and other prototypes. Some of our achievements are moving towards industrialization.

Zhang Zhijun has published more than 100 papers in important international journals (such as nature sub journal, IEEE Transactions) and conferences, 83 papers in SCI journals, and edit 2 English works. The total number of citations is 2998. It has accepted more than 100 invention patents and authorized 46 invention patents. Presided over or participated in more than 30 national key R&D projects, NSFC and horizontal projects. It has won one IEEE ICAL2011 International Conference Best Paper Award, ARM2020 International Conference Best Paper Award, ISAS2020 International Conference Best Sub conference Paper Award, China Science China Control Conference SCIS-CCC Posting Paper Nomination Award, and IROS2019 International Robot Flagship Conference Workshop Best Poster Award.

Prof. Junzhi Yu

Peking University, China

Fellow of IEEE, Winner of the National Outstanding Youth Fund

Research Areas:

1. Intelligent robots (bionic robots, mechatronic design, collective intelligence)
2. Advanced robot control (fuzzy system, artificial neural network, central pattern generator based locomotion control, etc)
3. Embedded vision (image processing, embedded systems, visual applications)

Prof. Simon X. Yang

Advanced Robotics and Intelligent Systems (ARIS) Laboratory

School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada

IEEE Senior Member

Prof. Simon X. Yang received the B.Sc. degree in engineering physics from Beijing University, China in 1987, the first of two M.Sc.  degrees in biophysics from Chinese Academy of Sciences, Beijing, China in 1990, the second M.Sc. degree in electrical engineering from the University of Houston, USA in 1996, and the Ph.D. degree in electrical and computer engineering from the University of Alberta, Edmonton, Canada in 1999. Prof. Yang joined the School of Engineering at the University of Guelph, Canada in 1999. Currently he is a Professor and the Head of the Advanced Robotics and Intelligent Systems (ARIS) Laboratory at the University of Guelph in Canada. 

Prof. Yang has diversified research expertise. His research interests include robotics, artificial intelligence, sensors and multi-sensor fusion, wireless sensor networks, intelligent control, machine learning, fuzzy systems, intelligent communication and transportation, and computational neuroscience. His significant research contributions can be reflected by his original and innovative work in biologically inspired intelligence with applications to real-time motion planning, tracking and control of various robotic systems, and various other engineering and biomedical systems. He has published over 600 referred papers, including over 330 journal papers. Prof. Yang he has been very active in various professional activities. He serves as the Editor-in-Chief of Intelligence & Robotics, and International Journal of Robotics and Automation; and an Associate Editor of IEEE Transactions on Cybernetics, IEEE Transactions of Artificial Intelligence, and several other journals. He has involved in the organization of many international conferences.

Speech Title: Bio-inspired Intelligent Approaches to Human-robot Interaction and Multi-robotic Systems

Abstract: Research on biologically inspired intelligence has made significant progress in both understanding biological systems and developing bionic engineering applications to robotics and control systems. In this talk, I will start with a very brief introduction to biologically inspired computational neurodynamics algorithms and their applications to early vision and sensory motion in biological systems. After that, several advanced intelligent approaches to human-robotic interaction/collaboration and teleoperation systems will be presented. After that, some recent research works on biologically inspired intelligent approaches to real-time navigation and cooperation of multiple autonomous robotic systems will be presented.