KEYNOTE SPAKERS
Prof. Jianshu ZHOU
National University of Singapore
Prof. CHEN Fei
The Chinese University of Hong Kong
Prof. Rosa CHAN
City University of Hong Kong
National University of Singapore
The Chinese University of Hong Kong
City University of Hong Kong
Embodied intelligence is often framed as a robotics problem focused on better sensing, better fusion, and better policies. Yet assistive robotics, neural interfaces, and wearable health systems represent the exact same loop with the sensors turned inward. Here, the body in the loop is biological, and the state space that matters most is not the environment, but the user’s neural dynamics and physiological state. Such systems are fundamentally co-embodied, as they cannot treat the human as an external disturbance, but must read noisy, non-stationary biological signals to act with the person in a unified physical loop. Drawing on research spanning computational neuroscience, electrophysiological decoding, and edge biosensing, this talk examines how user intent can be decoded reliably enough to close a physical control loop. We examine the transition from high-dimensional biological signals to wearable AIoT motion sensing, addressing how biologically constrained representations improve decoding fidelity and adaptive tracking over time. Finally, the talk challenges the current evaluation of human-in-the-loop systems. Standard machine learning benchmarks that report pooled, offline classification accuracy conceal the operational failure modes that matter most in physical deployment. We argue that true co-embodied intelligence demands evaluation frameworks centered on subject-specific uncertainty, few-shot online adaptation, and closed-loop stability under real-world non-stationarity.
Dr. Rosa H. M. Chan is a Professor in the Department of Electrical Engineering at City University of Hong Kong. Her research spans computational neuroscience, brain-computer interface, and multimodal sensing, with applications in health monitoring, sports performance, and rehabilitation. She received her Ph.D. in Biomedical Engineering (2011) from the University of Southern California, along with M.S. degrees in Biomedical Engineering, Electrical Engineering, and Aerospace Engineering. She is a co-recipient of the 2013 Outstanding Paper Award of the IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). Within the IEEE Engineering in Medicine and Biology Society, she was elected as Asia-Pacific Representative (2018-22) and Vice-President (2024-25). She also serves as an Associate Editor for IEEE TNSRE, IEEE Transactions on Biomedical Engineering, and IEEE Reviews in Biomedical Engineering.
Prof. Chen Fei received the B.S. degree in computer science from Xi’an Jiaotong University (XJTU), Xi’an, China, in 2006, the M.S. degree in computer science from Harbin Institute of Technology (HIT), Harbin, China, in 2008, and the Dr. Eng. degree in robotics from Fukuda Laboratory, Nagoya University, Nagoya, Japan, in 2012. Before joining CUHK, he was a researcher and founder of Active Perception and Robot Interactive Learning (APRIL) Laboratory at Italian Institute of Technology (IIT). He is currently leading Collaborative and Versatile Robots Laboratory (CLOVER) with the Department of Mechanical and Automation Engineering and CUHK T-Stone Robotics Institute. He has been acting as the PI of several EU and Italian national projects, e.g., EU FP7 AutoMAP, EU H2020 FET Chist-Era Learn-Real, VINUM and Learn-Assist as well as Hong Kong RGC ECS/GRF, ITC projects. His main research interest lies in robot mobile manipulation, robot grasping and manipulation, human-robot collaboration. He is an IEEE Senior Member. He is co-chair of IEEE Robotics and Automation Society Technical Committee on Neuro-Robotics Systems. He also serves as Associate Editor for IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Emerging Topics in Computational Intelligence, and Frontiers in Neurorobotics.
Prof. Jianshu Zhou is an Assistant Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), where he is establishing the Grasping and Manipulation Laboratory (G&M Lab) in 2026. Prior to joining NUS, he was a Postdoctoral Researcher in the Mechanical Systems Control Lab at the University of California, Berkeley. He also served as a Research Assistant Professor at The Chinese University of Hong Kong (CUHK), following a postdoctoral appointment in the same department. He received his Ph.D. in Mechanical Engineering from The University of Hong Kong.
His research focuses on robotics and mechatronics, with an emphasis on robotic grasping and manipulation, embodied intelligence, and multi-modal sensing, data acquisition, and interaction. His work aims to develop robust, high-performance robotic systems through hardware–software co-design for real-world applications. He has authored over 70 peer-reviewed publications with more than 1,900 citations (h-index: 22), including over 10 first-author papers in leading journals such as IEEE Transactions on Robotics, IEEE/ASME Transactions on Mechatronics, and Soft Robotics. He holds multiple U.S. patents, including two granted patents and several ongoing filings.
Dr. Zhou currently serves as a Technical Editor for IEEE/ASME Transactions on Mechatronics (T-Mech) and an Associate Editor for IEEE Robotics and Automation Letters (RA-L). He actively contributes to the robotics community through professional service roles, including Technical Editor, Associate Editor, Session Chair, and organizing committee member for major international conferences such as IEEE ICRA, IEEE RO-MAN, IEEE ICCA, and IEEE RCAR. He is a recipient of the ASME DSCD Rising Star Award. His research has been recognized with multiple Best Conference Paper Awards and Finalist honors, as well as the Gold Medal at the Geneva International Exhibition of Inventions. He has also received the IEEE Robotics and Automation Letters Outstanding Reviewer recognition. Dr. Zhou has secured competitive research funding, including support from the Hong Kong General Research Fund (GRF) as Principal Investigator.
Dr. You rose through the ranks at EFORT, previously serving as the company’s Chief Engineer, where he oversaw complex technical operations and industrial joint ventures (such as the partnership with Italy’s CMA Robotics). Under his leadership, EFORT transitioned away from systems integration to focus strictly on manufacturing complete units. He championed the “Great Tree” ecosystem model—anchoring the company deep into general-purpose technology (“roots”) and industrial robots (“the trunk”) to help partners innovate specific applications. Dr. You is a prominent voice in China’s advanced robotics sector. He frequently speaks at high-level economic and automation conferences, focusing on the infrastructure challenges of Embodied AI, specifically data acquisition, autonomous skill platforms, and cross-configuration data transfers.
Prof. Shuji Tanaka received B.E., M.E. and Dr.E. degrees in mechanical engineering from The University of Tokyo in 1994, 1996 and 1999, respectively. He was a Research Associate at Department of Mechatronics and Precision Engineering, Tohoku University from 1999 to 2001, an Assistant Professor from 2001 to 2003, and an Associate Professor at Department of Nanomechanics from 2003 to 2013. He is currently a Professor at Department of Robotics and Microsystem Integration Center. He was also a Fellow of Center for Research and Development Strategy, Japan Science and Technology Agency from 2004 to 2006, and a Selected Fellow from 2006 to 2018. In FY2017, he served as the President of Micro-Nano Science & Engineering Division, Japan Society of Mechanical Engineers (JSME). At present, he is serving as the Vice-Chair (Group 4 Chair) of Technical Program Committee (TPC) of IEEE International Ultrasonics Symposium and an AdCom member of IEEE UFFC Society. He served as General Chair of IEEE MEMS 2022 and TPC Chair of Transducers 2023. His research interests include MEMS sensors, acoustic wave devices, piezoelectric devices and materials, and wafer-level packaging and integration. He is an IEEE Fellow and a JSME Fellow.
Emeritus Professor Jack Dongarra received a Bachelor of Science in Mathematics from Chicago State University in 1972 and a Master of Science in Computer Science from the Illinois Institute of Technology in 1973. He received his PhD in Applied Mathematics from the University of New Mexico in 1980. He worked at the Argonne National Laboratory until 1989, becoming a senior scientist.
He now holds an appointment as University Distinguished Professor of Computer Science in the Computer Science Department at the University of Tennessee, has the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL), Turing Fellow in the Computer Science and Mathematics Schools at the University of Manchester, and an Adjunct Professor in the Computer Science Department at Rice University.
He specializes in numerical algorithms in linear algebra, parallel computing, the use of advanced-computer architectures, programming methodology, and tools for parallel computers. His research includes the development, testing and documentation of high quality mathematical software.
He has contributed to the design and implementation of the following open source software packages and systems: EISPACK, LINPACK, the BLAS, LAPACK, ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI. He has published approximately 300 articles, papers, reports and technical memoranda and he is coauthor of several books.
He was awarded the IEEE Sid Fernbach Award in 2004 for his contributions in the application of high performance computers using innovative approaches; in 2008 he was the recipient of the first IEEE Medal of Excellence in Scalable Computing; in 2010 he was the first recipient of the SIAM Special Interest Group on Supercomputing’s award for Career Achievement; in 2011 he was the recipient of the IEEE Charles Babbage Award; and in 2013 he was the recipient of the ACM/IEEE Ken Kennedy Award for his leadership in designing and promoting standards for mathematical software used to solve numerical problems common to high performance computing. He received the 2021 A. M. Turing Award from the Association of Computing Machinery, an award that is often described as the “Nobel Prize of computing.” He is a Fellow of the AAAS, ACM, IEEE, and SIAM and a foreign member of the Russian Academy of Sciences and a member of the US National Academy of Engineering.
Soft bio-integrated electronics have attracted great attentions due to the advantages of soft, lightweight, ultrathin architecture, and stretchable/bendable, thus has the potential to apply in various areas, especially in the field of biomedical engineering. By engineering the classes of materials processing and devices integration, the mechanical properties of the flexible electronics can well match the soft biological tissues to enable measuring bio signals and monitoring human body health. In this report, we will present materials, device structures, power delivery strategies and communication schemes as the basis for novel soft bio-integrated electronics. For instance, we will discuss a wireless, battery-free platform of electronic systems and haptic interfaces capable of softly laminating onto the skin to communicate information via spatio-temporally programmable patterns of localized mechanical vibrations. The resulting technology, which we refer as epidermal VR, creates many opportunities in social media/personal engagement, prosthetic control/feedback and gaming/entertainment. Other demonstrations will include skin-interfaces human machine interface for robotic VR, and skin like patches as sensors for healthcare monitoring.
Prof. Xinge Yu is the Associate Vice-President and Associate Director of Institute of Digital Medicine at City University of Hong (CityU), He is the Associate Director of Hong Kong Centre for Cerebro-cardiovascular Health Engineering. Prof Yu is the recipient of IEEE Technical Achievement Award, NSFC Distinguished Young Scientist Grant (Scheme A), RGC Research Fellow, NSFC Excellent Young Scientist Grant (Hong Kong & Macao), Innovators under 35 China (MIT Technology Review), New Innovator of IEEE NanoMed, MINE Young Scientist Award, Stanford’s top 2% most highly cited scientists etc. Prof. Yu is the Associate Editor of Science Advances, Microsystem & NanoEngineering, Bio-Design and Manufacturing etc. Xinge Yu’s research group is focusing on skin-integrated electronics and systems for VR and biomedical applications. He has published 200 papers in Nature, Nature Materials, Nature Biomedical Engineering, Nature Machine Intelligence, Nature Communications, Science Advances etc., and 50 patents filed/granted.
Dr. Xiong Lei is the Founder and CEO of Ningbo Joyson Telephix Technology Co., Ltd., and a leading expert in tactile and force sensing, multimodal fusion, and intelligent control. He earned his Ph.D. from the Pennsylvania State University and his Master’s degree from the Georgia Institute of Technology, and currently also serves as a postdoctoral researcher at Tsinghua University. As former Senior Director of Anker Innovations’ 2023 Lab, he led the development of embodied-intelligence perception systems all the way from technical definition to product realization, building deep, hands-on experience that spans academic research through to full industrialization. His current work centers on the development of dexterous robotic hands, with a focus on translating cutting-edge research into scalable, real-world industrial applications.