profile image

Speakers 2024

Keynote Speaker Ⅰ

  Speech Title: Research Progress and Reflection on Embodied Intelligence


Prof. Fuchun Sun

IEEE Fellow, CAAI Fellow and CAA Fellow

Tsinghua University, China

Biography: Sun Fuchun, Full Professor of the Department of Computer Science and Technology, Tsinghua University, IEEE/CAAI/CAA Fellow, Recipient of the National Outstanding Youth Fund; Serving as a member of the Academic Committee of Tsinghua University, Vice Chairman of the Professor Appointment Committee of the Department of Computer Science and Technology, and Director of the Intelligent Robotics Center of the Tsinghua University Artificial Intelligence Research Institute. He also served as the vice chairman of the Chinese Association of Artificial Intelligence, the supervisor of the Chinese Association of Automation, and the executive director of the Chinese Association of Cognitive Sciences. Serving as the editor in chief of international publications Cognitive Computation and Systems, AI and Autonomous Systems, executive editor of CAAI Artificial Intelligence, deputy editor in chief of IEEE Trans. on Fuzzy Systems, and editorial board member of Robots and Autonomous Systems and International Journal of Social Robots.


Abstract: Embodied intelligence is an important component of the new generation of artificial intelligence, emphasizing the interaction between perception and behavior in the physical world, including knowledge updating, growth, and developmental learning. It is an important combination of artificial intelligence and robotics technology. This report first reviews the development of embodied intelligence, proposes the concept of general agents, and introduces the main advancements made by the reporter team in the research of embodied intelligence across three aspects: embodied perception, cognitive decision-making, and embodied behavior, combined with general agents. The discussion then covers the application of embodied intelligence based on large models in 3C production lines. Finally, the report explores future directions for the development of embodied intelligence.


Keynote Speaker Ⅱ

  Speech Title: Magnetic Miniature Robots for Biomedicine: From Individual and Modular Designs to Microswarms




Prof. Li Zhang

IEEE Fellow

The Chinese University of Hong Kong, China


Biography: Li Zhang is a Professor in the Department of Mechanical and Automation Engineering (MAE) and a Professor by Courtesy in the Department of Surgery at The Chinese University of Hong Kong (CUHK). He is also a director of the Shenzhen Institutes of Advanced Technology (SIAT) of the Chinese Academy of Sciences (CAS) – CUHK Joint Laboratory of Robotics and Intelligent Systems. Dr. Zhang is elected as a Fellow of IEEE (FIEEE), Royal Society of Chemistry (FRSC), Asia-Pacific Artificial Intelligence Association (FAAIA), The Hong Kong Institution of Engineers (FHKIE), a member of the Hong Kong Young Academy of Sciences (YASHK), and an Outstanding Fellow of the Faculty of Engineering at CUHK. Dr. Zhang’s main research interests include small-scale robotics and their applications for translational biomedicine. He has authored or co-authored over 300 publications, including Nature Reviews Bioengineering, Science Robotics (3), Nature Machine Intelligence (3), Science Advances (10), Nature Communications (5), as the corresponding author. He currently serves as (or was) Senior Editor/Associate Editor/Editorial Board Member of ten international journals, such as IEEE T-RO, IEEE T-ASE, IEEE/ASME T-MECH, IEEE T-MRB, IEEE RA-L, Advanced Intelligent Systems (Wiley), International Journal of Extreme Manufacturing (IOP), Biomicrofluidics (AIP), Research (SPJ-AAAS), Med-X (Springer), and Bio-design and Manufacturing (Springer).

Abstract: Robotics at small scales has attracted considerable research attention both in its fundamental aspects and potential biomedical applications. As the characteristic dimensions of the robots or machines scaling down to the milli-/microscale or even smaller, they are ideally suited to navigating in tiny and tortuous lumens inside the human body which are hard-to-reach by regular medical devices. Although the materials, structural design, and functionalization of micro-/nanorobots have been studied extensively, several key challenges have not yet been adequately investigated for in vivo applications, such as adaptive locomotion in dynamic physiological environments, in vivo localization with clinical imaging modalities, the efficiency of therapeutic intervention, biosafety, and their autonomy for the intervention tasks. In this talk, I will first present our recent research progress on development of magnetic miniature robots, from individual and modular designs to the microswarms, for rapid endoluminal delivery. Then the key challenges and perspective of using magnetic miniature robots for localized therapy and clinically relevant applications with a focus on endoluminal procedures will be discussed.


Keynote Speaker Ⅲ

  Speech Title: Machine Learning for Brain-Computer Interfaces





Prof. Dongrui Wu

IEEE Fellow

Huazhong University of Science and Technology, China

Biography: Dongrui Wu (IEEE Fellow) is Professor and Deputy Director of the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China. Prof. Wu's research interests include brain-computer interface, machine learning, computational intelligence, and affective computing. He has more than 200 publications (12000+ Google Scholar citations; h=57). He received the IEEE Computational Intelligence Society  Outstanding PhD Dissertation Award in 2012, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2014, the IEEE Systems, Man and Cybernetics Society Early Career Award in 2017, the USERN Prize in Formal Sciences in 2020, the IEEE Transactions on Neural Systems and Rehabilitation Engineering Best Paper Award in 2021, the Chinese Association of Automation (CAA) Early Career Award in 2021, the Ministry of Education Young Scientist Award in 2022, and First Prize of the CAA Natural Science Award. His team won National Champion of the China Brain-Computer Interface Competition in two successive years (2021-2022). Prof. Wu is the Editor-in-Chief of IEEE Transactions on Fuzzy Systems.

Abstract: A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. Electroencephalograms (EEGs) used in BCIs are weak, easily contaminated by interference and noise, non-stationary for the same subject, and varying across different subjects and sessions. Thus, sophisticated machine learning approaches are needed for accurate and reliable EEG-based BCIs. This talk will introduce the basic concepts of BCIs, review the latest progress, and describe several newly proposed machine learning approaches for BCIs.


Keynote Speaker Ⅳ

    Speech Title: A Systematic Approach to Wearable Roboticd Development





Assoc. Prof. Haoyong Yu

National University of Singapore, Singapore

Biography: Dr. Yu Haoyong is an Associate Professor of the Department of Biomedical Engineering at the National University of Singapore. He received his Bachelor’s Degree and Master’s Degree from Shanghai Jiao Tong University and his PhD degree from Massachusetts institute of Technology (MIT). His current research interests include biomedical robotics and devices, rehabilitation engineering and assistive technology, service robots, human robot interaction, intelligent control and machine learning. Dr. Yu is the Associate Editor of IEEE Transactions on Automation Science and Engineering and IEEE/ASME Transactions on Mechatronics.

Abstract: With the rapid population aging, wearable Robotics, commonly known as Exoskeleton Robots, are believed to have great potential applications in many areas in both industry and Healthcare. However, the current market size of wearable robotics is still quite small compared with other robotics sectors due to the limitations in design, user experience, and high cost. At NUS Biorobotics Lab, we are developing a series of wearable robotics with wide range applications. We adopt a modular approach based a set of core technologies and components developed in the lab, which includes compliant actuation, cable mechanism, wearable sensors and learning based movement detection algorithms. We achieved better portability and better human robot interaction due to our compliant actuation and cable transmission and novel mechanism design. In this talk, we will give a brief introduction of some of our wearable robots and their potential applications.



More speakers are to be announced......