Plenary Speakers

Plenary Talk: 09:15-10:15 AM, Saturday, 31 October 2026

Title: Brain-Computer Interfaces and Biological Intelligence

Abstract: Brain-Computer Interface (BCI), serving as a bridge connecting biological intelligence with data intelligence and physical intelligence, represents an inevitable stage in the transition from “computational power dependence” to “intellectual dependence” in the era of artificial intelligence. It is driving the deep convergence of brain science research and intelligent technology revolution. Brain “reading” and “writing” are the core of BCI. The precise “reading” and “writing” mechanisms for brain-computer interface imaging and decoding neural signals are fundamental scientific challenges. Breaking through brain function and neural imaging, translation, and neural information writing to achieve efficient brain-computer information interaction is at the forefront of current scientific challenges and a key breakthrough for neural engineering, brain disease intervention, and brain-inspired computing. This report reviews the development history of AI, from Turing’s dream of “making machines think” to the rise of deep learning and the current era of large-scale models, highlighting AI’s significant breakthroughs in computational intelligence. Focusing on the technical roadmap for non-invasive BCI, this report examines the advancements in the development of transformative technologies for non-invasive brain-computer interface imaging and non-invasive acoustic-magnetic physical “reading” and “writing” technologies, revealing the decoding principles of neural electrical signals in relation to consciousness and movement intent. By integrating deep learning algorithms and real-time signal processing technologies, efficient and stable brain-machine interaction paradigms are constructed. Furthermore, the application potential of BCI imaging and regulation in visual reconstruction, motor intervention, and augmented reality is explored. Through interdisciplinary collaboration and innovation, brain-computer interface technology will provide transformative tools for brain disease diagnosis and treatment, embodied intelligence, human-machine collaborative intelligence, and the future ecosystem of “brain-to-brain communication.”

Biography: Dr. Hairong Zheng is an academician at the Chinese Academy of Sciences, serves as executive vice president of Nanjing University, and professor at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. He received his Ph.D degree in mechanical engineering from the University of Colorado at Boulder in 2006. He then joined the University of California, Davis, initially as a postdoctoral fellow, before becoming a project scientist in the Department of Biomedical Engineering. His research primarily focuses on brain-computer interface, medical imaging technology and instrumentation systems. Dr. Zheng is the recipient of the National Science Fund for Distinguished Young Scholars and has led several major scientific research projects. Additionally, he holds the position of director at the National Innovation Center for Advanced Medical Devices, and acts as vice president of the Chinese Society of Biomedical Engineering. For his contributions, Dr. Zheng has been honored with the National Science and Technology Award.

Keynote Speakers

Keynote Talk I: Saturday, 31 October 2026

Title: Cross-media Biosyncretic Robotic Intelligence through Integrating Living and Nonliving Systems

Abstract: Silicon-based robotic intelligence suffers the defects of slow learning rate, low migration ability, etc. while carbon-based biological intelligence shows exceptional advantages on learning and association abilities. Thus, it is significant to explore biosyncretic intelligence through interactive fusion between silicon-based and carbon-based intelligences. There are two approaches, “bottom-up” and “top-down”, to developing biosyncretic robotic intelligence. In the bottom-up way, the biosyncretic robotic intelligence is realized by growing an in vitro neural networks and training its connection plasticity via artificial stimulation based on the feedback of robotic behavior. In such way, the neural network is capable of performing some task, such as decision-making or recognition, and becomes a bio-intelligence controller. In contrast, the top-down approach refers to directly taking advantage of animals with bio-interfacing technologies, such as brain-machine interface (BMI). And, in such way, animals can be controlled by artificial stimulation and their sense and intention can be decoded from their brain activity for the fusion between the carbon-based intelligence and the silicon-based intelligence. Furthermore, animals can communicate and cooperate with electromechanical robots through such intelligence fusion. In this talk, the speaker will present some fundamental methods to develop biosyncretic intelligence in both bottom-up and top-down principles, and he will introduce some representative works in his group on the biosyncretic robotic intelligences developed in these two principles.

Biography: Lianqing Liu is a Professor at Shenyang Institute of Automation, Chinese Academy of Sciences. Currently his research interests include Biosyncretic systems, Micro/Nanorobotics, Intelligent control. He has published over 100 peer reviewed international journal papers and led more than 20 funded research projects as Principal Investigator. He was awarded the Early Career Award by the IEEE Robotics and Automation Society in 2011, Outstanding Young Scientist of Chinese Academy of Sciences in 2014, Rising Star Award of 3M-Nano Society in 2015, Talent Young Scholar Funds of NSFC in 2015, National Program for support of Top-Notch Young Professionals in 2015, Xiongyoulun Outstanding Youth Award in 2018, Distinguished Young Scholar Funds of NSFC in 2019 and continuing project in 2025, Xplore Prize in 2024. He is the winner of Best Student/Conference paper Award for ICRA, IROS, ROBIO, ICIRA, IEEE-NEMS, IEEE-CYBER, IEEE-NANOMED and IEEE-3M-NANO, and delivered Plenary/Keynote talks at ICRA, IROS, IEEE-NANO, IEEE-NANOMED, IEEE-NEMS, ICIUS, MARSS and so on. He is associate editors of Fundamental Research, Cyborg and Bionic Systems, Mechatronics, IET Cyber-Systems and Robotics, Control Theory and Applications. He has been elected as the vice president of IEEE Robotics and Automation Society for the term of 2018-2019, served as a member of long range planning committee of RAS.

Keynote Talk II: Saturday, 31 October 2026

Title: Biophysics-informed design of biohybrid microrobots

Abstract: Biohybrid microrobots integrate biological components with synthetic structures to navigate complex biological environments, for example, for the delivery of drugs, microsurgery and in vivo diagnostics. In this talk, I will present a biophysics-informed design framework for biohybrid microrobots by connecting biophysical principles with biohybrid solutions. We first identify the biophysical constraints imposed by the human body that limit microrobot integrity, locomotion, navigation and functionality. We then examine the biophysical mechanisms through which biological cells, microorganisms and their derivatives adapt to these challenges, and explore how these can be utilized to improve the performance of microrobots. Building on these insights, we describe how biohybrid microrobots translate biophysical strategies into engineering solutions across four design domains: deformation, actuation, navigation and programming. Finally, we discuss persisting in vivo challenges, key considerations for clinical translation and future developments.

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). Dr. Zhang’s primary research interests include small-scale robotics and their applications for translational biomedicine. He has authored or co-authored over 400 publications (H-index: 96), including Science Robotics, Nature Machine Intelligence, Nature Reviewers Bioengineering, Nature Materials, Nature Biomedical Engineering, Nature Synthesis as the corresponding author. His research work on artificial bacterial flagella was indexed by the Guinness Book of World Records 2012 for the “Most Advanced Mini Robot for Medical Use.” And his research works on magnetic slime robot and microrobotic swarm for endovascular application was selected as “Top 10 Innovation and Technology News in Hong Kong” in 2022, 2023 and 2024. Dr. Zhang is elected as Fellow of ASME, IEEE, RSC, AAIA, HKIE, and is recognized as a distinguished young scholar of China-America Frontiers of Engineering in CAFOE 2026. He serves as Senior Editor for IEEE T-ASE and IEEE T-RO, and as Associate Editor for Science Advances (AAAS).

Keynote Talk III: Saturday, 31 October 2026

Keynote Talk IV: Saturday, 31 October 2026

Title: Biohybrid Robotics: Concept, Developments, Challenges, and Perspectives

Abstract: As robotic applications expand from industrial scenarios to service and biomedical scenarios, robots are required to function in organism-involved environments. Therefore, biological systems have become an intuitive source of design principles for robotic systems. Among these biology-oriented approaches, biomimetic robotics primarily reproduces biological forms, and bioinspired robotics abstracts biological mechanisms to achieve robotic function. However, in physiological and medical settings, these conventional robotic strategies remain limited, as effective function requires direct, adaptive and sustained interaction with living tissues. This demand motivates the conceptual shift from imitating or abstracting biology toward directly hybridizing biology and robotics, termed as biohybrid robotics. Biohybrid robots can be considered as robotic systems that hybridize engineered components and living organisms or functional biological entities, enabling biological activity and engineered mechanisms to jointly contribute to actuation, sensing and control. Several recent studies fall within the scope of biohybrid robotics as defined here, and are introduced across three physical scales, including microbial scale, tissue scale, and organ scale. We anticipate continued advances in hybridizing biology and robotics, and envision the development of biohybrid robotics as a new era of robotics.

Biography: Zeyang Xia is a Professor with School of Mechanical Engineering, Shanghai Jiao Tong University, China. He received the B. Sc. degree from Shanghai Jiao Tong University, China in 2002, and the Ph. D. degree from Tsinghua University, China in 2008. Afterwards, he had been working in Nanyang Technological University, Singapore and Indiana University Purdue University Indianapolis, U.S.. He joined Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences in 2012, where he was a CAS Distinguished Professor, Professor with State Key Laboratory of Biomedical Imaging Science and System, Director of Soft Robotics Research Center and Director of International Joint Laboratory for Soft Medical Robotics. His research interests include robotics and biomechanics, specifically biomedical robotics and artificial intelligence, soft robotics, humanoid robotics, and computational biomechanics. He is/was the PI of over 30 research grants, including National Key Research and Development Project and National Nature Science Funds Key Project. He has published two monographs and over 140 research papers and has been granted over 50 patents. He was the winner of Wu Wenjun Artificial Intelligence Natural Science Award in 2017, and Xiong Youlun Excellent Young Scholars Award in 2019. He serves/served as the editorial board members of Innovation Informatics, IEEE/ASME Transactions on Mechatronics, Robot, SmartBot, and the General Chair of IEEE RCAR 2019. He is a Senior Member of IEEE/CIE/CAA, a Distinguished Member of CCF, and a Fellow of IET.