Keynote Speaker
Prof. Pietro Valdastri, University of Leeds, UK
Bio: Pietro Valdastri is Full Professor and Chair in Robotics and Autonomous Systems at the University of Leeds. He directs the Science and Technologies Of Robotics in Medicine (STORM) Lab, focusing on intelligent robots to fight cancer, the Institute of Robotics, Autonomous System and Sensing (IRASS), and the Robotics at Leeds network. He received his Laurea degree in Electronic Engineering from the University of Pisa in 2001 and his PhD in Biomedical Engineering from Scuola Superiore Sant’Anna in 2006. After the PhD, he became Assistant Professor in Biomedical Engineering at the BioRobotics Institute of Scuola Superiore Sant’Anna. In 2011, Prof Valdastri moved to Vanderbilt University as an Assistant Professor in Mechanical Engineering until 2016, when he relocated to Leeds.
He has published more than 150 peer reviewed journal papers in the field of medical robotics and has been principal investigator on grants in excess of $24M supported by NSF, NIH, ERC, EU-H2020, Cancer Research UK, The Royal Society, EPSRC, Innovate UK and industry, including the NSF CAREER Award with the proposal “Lifesaving Capsule Robots” in 2015, the ERC Consolidator Grant Award with the proposal “NoLiMiTs – Novel Lifesaving Magnetic Tentacles” in 2019, and the KUKA Innovation Award for his robotic colonoscopy platform in 2019. Prof. Valdastri is a Royal Society Wolfson Research Fellow, a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the Editor for Medical and Rehabilitation Robotics of the IEEE Robotics and Automation Letters, and a member of the steering committee of the International Society for Medical Innovation and Technology (iSMIT). STORM Lab’s research has been featured by several news outlets, including the BBC, The Times, The Washington Post, The Financial Times, Bloomberg, New Scientist, The Spectator, WIRED, IEEE Spectrum, Medgadget, Daily Mail, The Engineer, Ingenia Magazine, Medical Design Technology Magazine, Medical Xpress, Newswise, NSF Science Now. Prof Valdastri also completed a successful entrepreneurial cycle with WinMedical s.r.l., a company he co-founded in 2009 and that was acquired by a larger enterprise in 2017. He recently started a new company, Atlas Endoscopy Limited, to bring his robotic colonoscopy platform to patients.
Speeech Title: Magnetic Surgical Robots: A “Fantastic Voyage” deep inside the human body
Abstracr: Magnetic fields offer the possibility of manipulating objects from a distance and are ideal for medical applications, as they penetrate human tissue without inflicting any harm on the patient. Magnetic fields can be harnessed to actuate surgical robots, enhancing the capabilities of surgeons in reaching deep into the human anatomy through complex winding pathways, thus providing minimally invasive access to organs that are out of reach with current technologies. In this talk, we will explore various robotic architectures based on magnetic control, specifically designed for lifesaving clinical applications. These architectures include a magnetic flexible endoscope for painless colonoscopy, soft magnetic tentacles personalized for reaching peripheral areas of the lung and navigating the pancreatic duct, magnetic vine robots for endoluminal exploration, and magnetic “fusilli” robots designed for collaborative bimanual tasks in a confined workspace. We will also discuss enabling technologies, intelligent control, potential levels of computer assistance, the path to first-in-human trials, and highlight the future challenges associated with this ongoing Fantastic Voyage.
Prof. Su Rong, Nanyang Technological University, Singapore
Bio: Rong Su is the Professor of Systems Intelligence and Control at the Nanyang Technological University (NTU). He received his B.S. degree from the University of Science and Technology of China in 1997 and M.A.S. and Ph.D. degrees from the University of Toronto in 2000 and 2004, respectively. He was affiliated with the University of Waterloo and Eindhoven University of Technology, before joining the faculty at NTU in 2010. Currently, he holds a full professor position, leading the Centre of Systems Intelligence and Efficiency (CSIE) in the School of Electrical & Electronic Engineering (EEE) at NTU. He is also the Program Director of the EEE Master of Science Program in Computer Control and Automation (CCA) and the NTU Lead of the Program Management Committee (PMC) of the KTH-NTU Joint PhD Program. His research interests include multi-agent systems, discrete-event system theory, model-based fault diagnosis, cyber security analysis and synthesis, control and optimization of complex networks with applications in flexible manufacturing, intelligent transportation, human-robot interface, power management and green buildings. In the aforementioned areas he has more than 330 journal and conference publications, 2 monographs, 18 granted/filed patents. Currently, he is serving as an associate editor for IEEE Transactions on Cybernetics, Automatica (IFAC), Journal of Discrete Event Dynamic Systems: Theory and Applications, and Journal of Control and Decision. He was the chair of the Technical Committee on Smart Cities in the IEEE Control Systems Society in 2016–2019, chair of the Control Systems Chapter, Singapore in 2020–2021, and a co-chair of Technical Committee on Automation in Logistics in the IEEE Robotics and Automation Society in 2021–2024. Dr Su is the recipient of several best paper awards, including 2021 Hsue-shen Tsien Paper Award from IEEE/CAA Journal of Automatica Sinica, and an IEEE Distinguished Lecturer for IEEE Robotics and Automation Society.
Speech Title: A Centralized Planning and Distributed Execution Method for Shape Filling with Homogeneous Mobile Robots
Abstract: Distributed pattern formation of a multi-robotic system is a widely studied topic in the research community, which has found applications in almost every part of our life. How to use robots equipped with limited sensors to form complex patterns is both theoretically and practically important. In this talk, we study the problem of forming complex shapes with functionally limited mobile robots, which have to rely on other robots to precisely locate themselves. The goal is to decide whether a given shape can be filled by a given set of robots; in case the answer is yes, to complete a shape formation process as fast as possible with a minimum amount of communication. Traditional approaches either require global coordinates for each robot or are prone to failure when attempting to form complex shapes beyond the capability of given approaches - the latter calls for a decision procedure that can tell whether a target shape can be formed before the actual shape-forming process starts. In response to this call for solutions, we develop a method that does not require global coordinate information during the execution process and can effectively decide whether it is feasible to form the desired shape. The latter is achieved via a planning procedure that is capable of handling a variety of complex shapes, in particular, those with holes, and assigning a simple piece of scheduling information to each robot, facilitating subsequent distributed execution, which does not rely on the coordinates of all robots but only those of neighboring ones. The effectiveness of our shape-forming approach is vividly illustrated in several simulation and field case studies.
Prof. Fumiya Iida, University of Cambridge, UK
Bio: Fumiya Iida is a Professor o Robotics at Department of Engineering, University of Cambridge, the director of Bio-Inspired Robotics, and a Global Fellow of the University of Tokyo. He received his bachelor and master degrees in mechanical engineering at Tokyo University of Science (Japan, 1999), and Dr. sc. nat. in Informatics at University of Zurich (2006). In 2004 and 2005, he was also engaged in biomechanics research of human locomotion at Locomotion Laboratory, University of Jena (Germany). From 2006 to 2009, he worked as a postdoctoral associate at the Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology in USA. In 2006, he awarded the Fellowship for Prospective Researchers from the Swiss National Science Foundation, and in 2009, the Swiss National Science Foundation Professorship for an assistant professorship at ETH Zurich from 2009 to 2015. He was a recipient of the IROS2016 Fukuda Young Professional Award, Royal Society Translation Award in 2017, Tokyo University of Science Award in 2021. His research interest includes biologically inspired robotics, embodied artificial intelligence, and biomechanics, where he was involved in a number of research projects related to dynamic legged locomotion, dextrous and adaptive manipulation, human-machine interactions, and evolutionary robotics.
Speech Title: Info-bodiment: Informationalization of robot embodiment for the next generation AI Robots
Abstract: There is growing interest in applying AI technologies to the control of intelligent robotic systems. While this research has led to promising developments, it still faces major challenges due to its heavy reliance on learning from limited datasets—often dominated by visual information. In this talk, I will introduce "Info-Embodiment" as a new research framework for realizing Embodied Intelligence, along with its underlying technological foundations. As advances in soft robotics and functional materials enable deeper integration between the informational and physical realms, we are beginning to see the emergence of novel forms of embodied intelligence. Within this evolving landscape, I will explore how rapidly advancing fields such as machine learning can help accelerate progress. Going beyond conventional models of body control and AI as abstract computational systems, this approach positions the body itself as an active site of information processing and generation, opening new possibilities for intelligent behavior.
Prof. Kai Cai, Osaka Metropolitan University, Japan
Bio: Kai Cai received the B.Eng. degree in Electrical Engineering from Zhejiang University, Hangzhou, China, in 2006; the M.A.Sc. degree in Electrical and Computer Engineering from the University of Toronto, Toronto, ON, Canada, in 2008; and the Ph.D. degree in Systems Science from the Tokyo Institute of Technology, Tokyo, Japan, in 2011. He is currently a Professor at Osaka Metropolitan University. Previously, he was an Associate Professor at Osaka City University (2014--2020), an Assistant Professor at the University of Tokyo (2013--2014), and a Postdoctoral Fellow at the University of Toronto (2011--2013).
Dr. Cai's research interests include discrete-event systems, cyber-physical systems, and networked multi-agent systems. He is the author of “Invitation to Supervisory Control” (KDP 2024), co-author (with Z. Lin) of “Directed Cooperation”, co-author (with W.M. Wonham) of “Supervisory Control of Discrete-Event Systems” (Springer 2019) and “Supervisor Localization” (Springer 2016). He is serving as a Senior Editor for Nonlinear Analysis: Hybrid Systems and an Associate Editor for IEEE Transactions on Control of Network Systems. He served as the Chair for the IEEE CSS Technical Committee on Discrete Event Systems (2020~2024) and an Associate Editor for the IEEE Transactions on Automatic Control (2018~2024). He was the recipient of the Pioneer Award of SICE in 2021, the Best Paper Award of SICE in 2013, the Best Student Paper Award of the IEEE Multi-Conference on Systems and Control, and the Young Author’s Award of SICE in 2010.
Speech Title: Types of Graph Laplacian Matrices and their Roles in Cooperative Control of Multi-Agent Systems
Abstract: In Systems Control and Robotics, many cooperative control problems of multi-agent systems have been actively studied in the past decades. Common in the formulation and resolution of these problems, a graph Laplacian matrix plays a key role. A graph Laplaican matrix is an important representation of graph topology, which describes the interconnection structure of the agents. Depending on the field of the entries, there are three types of Laplacian matrices: standard Laplacian (nonnegative diagonal entries and nonpositive off-diagonal entries), signed Laplacian (arbitrary real entries), and complex Laplacian (arbitrary complex entries). This talk will introduce these different types of Laplacian matrices, and their roles in modeling and solving different sets of cooperative control problems. Particular attention will be given to their algebraic properties that are fundamental in characterizing stability and performance of the respective solution algorithms.
Prof. Tetsuyou Watanabe, Kanazawa University, Japan
Bio: Tetsuyou Watanabe is a professor with Kanazawa University. He received the B.S., M.S., and Dr.Eng. degrees in mechanical engineering from Kyoto University, Kyoto, Japan, in 1997, 1999, and 2003, respectively. From 2003 to 2007, he was a Research Associate with the Department of mechanical Engineering, Yamaguchi University, Japan. From 2007 to 2011, he was an assistant professor with Division of Human and Mechanical Science and Engineering, Kanazawa University. From 2011 to 2018, he was an associate professor with Faculty of Mechanical Engineering, Institute of Science and Engineering, Kanazawa University. Since 2018, he has been a professor with Kanazawa University. From 2008 to 2009, he was a visiting researcher at Munich University of Technology. His current research interests include robotic hand, grasping, object manipulation, medical and welfare sensors, surgical robots, and user interface. He got several awards including best paper award at Transactions of the Society of Instrument and Control Engineers and World Robot Summit Second Prize of World Robot Challenge Industrial Robotics Category Second Prize of World Robot Challenge Industrial Robotics Category.