Professor Aike Guo

Academician of Chinese Academy of Sciences

University of Chinese Academy of Sciences, China

BIO: Guo Aike, Member of the CAS , as well as a member of the academic department of the Chinese Academy of Medical Sciences. In 1965, he graduated from the Biophysics  of Moscow University in the Soviet Union. In 1979, he received a doctor's degree in natural science from the University of Munich in Germany ( Dr. rer.nat,  Summa Cum Laude). From 1982 to 1984, 1987, 1993 to 1994, he was a visiting scholar of the Institute of Biocybernetics of the Max Planck Society in Germany and the University of Wurzburg in Germany. Since 1965, he has successively served as a research intern, assistant researcher, associate researcher, researcher, director of the Visual Information Processing Research Department, director of the Learning and Memory Laboratory, director of the Neurobiology Department, director of the Academic Committee of the Open Laboratory of Visual Information Processing, and director of the Academic Committee of the State Key Laboratory of Brain and Cognitive Sciences in the Institute of Biophysics, Chinese Academy of Sciences. Since 1999, he has successively served as the senior researcher of the Center for Excellence and Innovation in Brain Science and Intelligent Technology (Institute of Neuroscience) of the Chinese Academy of Sciences, the leader and deputy director of the Learning and Memory Laboratory. From 1999 to 2001, he served as the director of Asia Pacific IBRO. He has successively served as the chief scientist of the “973” Plan（Ministry of Science and Technology） "Basic Research on Brain Development and Plasticity", the “973” Plan "Research on the Plasticity of Brain Structure and Function", and the CAS Strategic Leading Science and Technology Special (Category B) Brain Science Frontier and Cross Research Project "Brain Function connection mapping". The final evaluation of the above projects all is excellent. He was a member of the 14th to 15th Standing Committee of the Department of Life Sciences and Medicine of the Chinese Academy of Sciences.

Guo Aike's research field is Brain and Cognitive Neuroscience. He is a pioneer in the field of Drosophila cognitive research and biological cybernetics research. In 1993, he established the first laboratory in China to study learning and memory using fruit fly Drosophila as a model animal. From the perspective of evolution and selection, from the combination of gene, brain and behavior, at the molecular, cellular, circuit and behavior levels, he revealed the brain mechanisms at the molecular, cellular, circuit and system levels of learning and memory, pattern recognition, selective attention, Figure-Ground  motion perception, group flight control and self-organization, male Drosophila's sexual courtship behavior, and especially initiated the value based decision making research of Drosophila. The academic idea of developing autonomous intelligent UAV cluster on the basis of Drosophila compound eye high-speed and dynamic vision bionics is proposed; He and his team had developed the research method of microscopic neural connectome by means of combining electron microscopy with ultrathin serial sections. He has won the Outstanding Achievement Award of the Asia Pacific Neural Network Association, the Science and Technology Progress Award of Ho Leung Ho Lee and the Outstanding Scientific and Technological Achievement Award of the Chinese Academy of Sciences.  His scientific dream is to "seek the essence of brain intelligence and illuminate the way of brain like intelligence" from the micro, meso, macro and even cosmological scales.

Title: Exploring the Essence of Brain Intelligence and Illuminating the Path of Brain like Intelligence

Abstract: From the creation of the universe to the explosion of life, to intelligent evolution, and to artificial intelligence, this is a long river of evolution. The times are asking, where do the brain and mind come from and where will they go?  What is the future and destiny of human civilization? How can brain intelligence and artificial intelligence illuminate each other? Can artificial intelligence lead to the "mind" through a completely different path from biological evolution? How does intellectual creativity evolve into New Quality Productivity? The core of these questions is still how the human brain works as a whole? Here, I will outline a dialectical unity of complexity and simplicity at the micro- meso -macro- cosmological scale.

Professor Fakhri Karray

Fellow of the Canadian Academy of Engineering 

IEEE Fellow

University of Waterloo, Canada

BIO: Fakhri Karray is the inaugural co-director of the University of Waterloo Artificial Intelligence Institute and served as the Loblaws Research Chair in Artificial Intelligence in the department of electrical and computer engineering at the University of Waterloo, Canada. He is also Professor of Machine Learning and held  the position of Provost at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), a research-oriented artificial intelligence (AI) institution in Abu Dhabi, UAE. Fakhri's research focuses on operational and generative AI, cognitive machines, natural human-machine interaction, and autonomous and intelligent systems, with applications to virtual care systems, cognitive and self-aware devices, and predictive analytics in supply chain management and intelligent transportation systems. Notably, Fakhri and his research team's work on deep learning-based driver behavior recognition and prediction has gained recognition in The Washington Post, Wired Magazine, Globe and Mail, CBC radio, and Canada's Discovery Channel. He also holds editorial roles in major publications related to intelligent systems and information fusion. Fakhri's latest textbook, "Elements of Dimensionality Reduction and Manifold Learning," was published by Springer Nature in early 2023. In 2021, he was honored by the IEEE Vehicular Technology Society (VTS) with the IEEE VTS Best Land Transportation Paper Award for his pioneering research on enhancing traffic flow prediction using deep learning and AI. Furthermore, his research on federated learning in communication systems earned him and his co-authors the 2022 IEEE Communication Society's MeditCom Conference Best Paper Award. Fakhri is also the co-founder and Chief Scientist of Yourika.ai, a provider of AI-based online learning systems. He holds fellowship status in the IEEE, the Canadian Academy of Engineering, and the Engineering Institute of Canada. Additionally, he has served as a Distinguished Lecturer for the IEEE and is a Fellow of the Kavli Frontiers of Science. Fakhri earned his Ph.D. from the University of Illinois Urbana-Champaign, USA.

Title: Prospects on Generative  AI: Milestones and Societal Impact

Abstract: The presentation discusses recent developments and notable progress in Artificial Intelligence (AI), specifically Generative Artificial Intelligence (GAI). Remarkable achievements in this field, including ChatGPT, BARD, LLaMA, and other generative AI engines, coupled with advancements in machine learning and AI tools, suggest we stand on the brink of a transformative technological revolution with unprecedented implications for humanity. Projections indicate that AI could boost the global GDP by as much as 20% by 2025, equivalent to over $15 trillion in growth within the coming years. These advancements have significantly influenced innovation in various domains, such as the Internet of Things, autonomous machinery, robust chatbots, virtual assistants, human-machine interfaces, extensive language models, real-time translators, cognitive robotics, accurate disease diagnosis, remote healthcare monitoring, financial market forecasting, and Fintech, among others. While AI encompasses a range of interconnected technologies, all aimed at emulating aspects of human intelligence and decision-making, transformer algorithms are recognized as the driving force behind AI's explosive expansion, permeating nearly every sector of the modern global economy. The presentation outlines key milestones that have driven the current GAI growth, emphasizing the roles of academic institutions, industry, and government. Additionally, it delves into critical concerns related to security, governance, and privacy, highlighting the potential for significant negative impacts on society and end users if not promptly and effectively addressed.

Professor Simon X. Yang

University of Guelph, Canada

BIO: 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 & Intelligent Systems (ARIS) Laboratory at the University of Guelph in Canada.  Prof. Yang has diversified research expertise. His research interests include intelligent systems, robotics, control systems, sensors and multi-sensor fusion, wireless sensor networks, intelligent communications, intelligent transportation, machine learning, and computational neuroscience. He has published over 550 academic papers, including over 350 journal papers. He has been listed on the World’s Top 2% Researchers by Stanford’s Standardized Citation Indicators from 2021 to 2023.  Prof. Yang he has been very active in professional activities. Prof. Yang has served as the Editor-in-Chief of Intelligence & Robotics, and some other journals; and an Associate Editor of IEEE Transactions on Cybernetics, IEEE Transactions on Artificial Intelligence, and several other journals. He has been involved in the organization of many international conferences.

Title: Advanced Intelligent Approaches to Agricultural and Environmental Engineering Systems

Abstract: Research on intelligent systems, particularly biologically inspired intelligence, has made significant progress in both understanding the biological systems and developing bionic engineering applications to various agricultural engineering systems. In this talk, I will start with a very brief introduction to the general intelligent systems, with a focus on some biologically inspired intelligent systems approaches. Then I will present on our current research on intelligent systems with applications to various agricultural engineering systems, such as intelligent real-time monitoring and control of livestock odors with a wireless e-noses network system, intelligent monitoring and control of the drying processes in meat and tobacco industries, intelligent data analysis and classifications of oranges and tobacco leaves based on near infrared spectroscopy, and intelligent robotic systems for harvesting of tomatoes and other vegetables and fruits. In addition, the cutting-edge deep learning methodologies, such as the Spatio-Temporal Attention Long Short Term Memory (STA-LSTM) model and Spatio-Temporal Attention Gated Recurrent Unit (STA-GRU) model, are developed for flood forecasting and monitoring of water quality and other environment factors, heralding a significant leap forward in environmental modeling techniques.

Professor Xinyu Wu

Outstanding Young Scholars of National Natural Science Foundation of China

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China

BIO: Xinyu Wu, PhD supervisor, Professor, recipient of the National Outstanding Youth Fund, leader among the National Ten Thousand Talents Program, and a member of the Expert Group for the Intelligent Robotics Special Project under China's National Key R&D Program during the 13th and 14th Five-Year Plans. Currently, Dr. Wu serves as the Deputy Director of the Institute of Integration Technology at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, the Director of the Center for Intelligent Bionics, and the Head of the Guangdong Provincial Key Laboratory of Intelligent Robots and Systems. Currently, his primary research focuses on the fundamental theories and key technologies of human-robot integrated service robots. He has published over 260 papers in prestigious international journals such as IEEE Transactions on Robotics (TRO), IEEE Transactions on Automation Science and Engineering (TASE), IEEE Transactions on Industrial Electronics (TIE), and IEEE Transactions on Systems, Man, and Cybernetics (TSMC), as well as in major international robotics conferences including ICRA and IROS. He has also authored two English monographs. Dr. Wu has consistently been included in Stanford University and Elsevier's global list of the top 2% most influential scientists. He was ranked first in receiving the First Prize of Guangdong Province Science and Technology Progress Award (2022), the First Prize of Science and Technology Award from the China Instrument and Control Society (2018), and the First Prize of Shenzhen Science and Technology Progress Award (2018), among other scientific research accolades. He serves as a Council Member of the Chinese Association of Automation and the Council Member of the China Instrument and Control Society. 

Title: Development and Reflections on Exoskeleton Robotics

Abstract: Exoskeleton robots hold significant application prospects in areas like assisting the elderly and disabled individuals, as well as material handling in logistics, where the degree of human-robot integration directly impacts the efficacy of aid and mobility support. The report comprehensively introduces the cutting-edge research and current development status both domestically and abroad in lower limb exoskeletons across various specialized domains. It consolidates and summarizes the common challenges confronted in the advancement of human-robot integrated exoskeleton systems. With a focus on exemplary systems developed by the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences (SIAT CAS), including self-balancing lower limb exoskeletons, flexible-stiffness adaptive exoskeletons, and load-assist exoskeletons, the report delves into crucial technologies such as coupling modeling of human-exoskeleton systems, structurally compatible design, motion intent recognition, and high-precision force-position control. Ultimately, it assesses the technological trajectories for achieving deeper integration and synergy between humans and exoskeletons.