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  <title>DARS 2026 – Distributed Autonomous Robotic Systems 2026</title>
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    <h1>Keynote</h1>
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        <img class="avatar" src="assets/img/speaker/iida_2026.jpg" alt="Fumiya Iida photo">
        <h3>Fumiya Iida</h3>
        <h1>Bio-Inspired Robotics Laboratory,<br>University of Tokyo and University of Cambridge</h1>
        <br>
        <p class="talk-title-line"><span class="item-label">Talk Title:</span> <span class="item-text">Distributed Tactile Intelligence for Bio-Inspired Soft Robots</span></p>
        <p class="abstract-line"><span class="item-label">Abstract:</span> <span class="item-text">Soft robotics has advanced rapidly through the development of deformable functional materials, enabling capabilities such as adaptive locomotion, dexterous manipulation, self-healing, morphing, and mechanical growth. These innovations have broadened the applicability of robotic systems, particularly in environments that require compliance, robustness, and safe interaction with humans. However, the very properties that make soft robots powerful--their continuum nature and high-dimensional deformation--also introduce fundamental challenges in sensing, modeling, planning, and control. In this talk, I present a shift from centralized control toward distributed tactile intelligence, achieved through the tight integration of sensorized soft materials and data-driven methodologies. By embedding dense, multimodal sensing directly into soft bodies and leveraging machine learning for embodied signal processing, we enable localized perception-action loops that allow robots to interpret rich physical interactions and adapt their behavior in real time. This approach reframes the body itself as a computational resource, reducing reliance on explicit modeling and enabling more robust operation in uncertain, unstructured environments. I will highlight several projects from our laboratory that illustrate this paradigm, including soft systems for assistive technologies, adaptive manipulation, and autonomous operation under complex environmental conditions. These examples demonstrate how material-level sensing and distributed intelligence can unlock new functionalities that are difficult to achieve with conventional architectures. Looking forward, the convergence of soft materials, embedded sensing, and data-centric intelligence points toward a new generation of robotic systems that are inherently interactive, context-aware, and resilient--bringing us closer to the adaptive capabilities observed in biological organisms.</span></p>
        <p><span class="item-label">Biography:</span> <span class="item-text">Fumiya Iida is a Professor at School of Engineering, the University of Tokyo, Professor of Robotics at the University of Cambridge, and the director of Bio-Inspired Robotics Laboratory. 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 until 2015. He was also a Professor of Robotics at the University of Cambridge until 2025. 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.</span></p>
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         <img class="avatar" src="assets/img/speaker/Xavier_Defago.jpeg" alt="Xavier Defago photo">
          <h3>Xavier Defago</h3>
          <h1>Institute of Science Tokyo</h1>
          <br>
          <p class="talk-title-line"><span class="item-label">Talk Title:</span> <span class="item-text">TBA</span></p>
          <p class="abstract-line"><span class="item-label">Abstract:</span> <span class="item-text">TBA</span></p>
          <p><span class="item-label">Biography:</span> <span class="item-text">
            Xavier Defago is a professor at the School of Computing, Institute of Science Tokyo, and a member of the Center for Cybersecurity Research and Education at that institution.

            He obtained master (1995) and PhD (2000) in computer science from the Swiss Federal Institute of Technology in Lausanne (EPFL) in Switzerland. He worked as a research intern at NEC C&C central research laboratories in 1995-1996. From 2000 to 2016, he was a faculty member at the Japan Advanced Institute of Science and Technology (JAIST). From 2002 to 2006, he has also been a PRESTO researcher for the Japan Science and Technology Agency (JST), and in 2013 an invited researcher for CNRS (France) at Sorbonne University (Paris, France) and at Inria Sophia Antipolis (France).

            He is a member of the IFIP working group 10.4 on dependable computing and fault-tolerance. He served as program chair of several international conferences in distributed systems and dependability (DSN 2023, SRDS 2014, ICDCS 2012, SSS 2011); as general chair (OPODIS 2023, SSS 2018); and as steering committee chair of OPODIS (2025-2029); as a steering committee member of DSN (2026-).

            His research interests include various aspects of dependable and secure distributed systems, cooperative robotics, embedded systems, and programming languages. He is involved in joint research on blockchain-based distributed energy trading with Mitsubishi Electric Corporation; on multi-agent pathfinding and smart factories with Murata Machinery; and on the formal verification of multi-robots algorithms with Sorbonne University and University of Lyon I (France).
          </span></p>
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    <h1>Perspective</h1>
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      <article class="person-card">
        <img class="avatar" src="assets/img/speaker/Kaoru_Yamamoto.jpg" alt="Kaoru Yamamoto photo">
        <h3>Kaoru Yamamoto</h3>
        <h1>Kyushu University</h1>
        <br>
        <p class="talk-title-line"><span class="item-label">Talk Title:</span> <span class="item-text">TBA</span></p>
        <p class="abstract-line"><span class="item-label">Abstract:</span> <span class="item-text">TBA</span></p>
        <p><span class="item-label">Biography:</span> <span class="item-text">Kaoru Yamamoto received her bachelor's and master's degrees in architectural engineering from Kyoto University, Japan, and her Ph.D. in control engineering from the University of Cambridge, UK. Following postdoctoral positions at the University of Minnesota and Lund University, she joined Kyushu University, Japan, in 2018, where she is currently an associate professor in the Faculty of Information Science and Electrical Engineering. She also serves as Co-Chair of the IEEE Robotics and Automation Society (RAS) Technical Committee on Robot Control. Her research focuses on the theory and control of multi-agent and swarm robotic systems, with particular emphasis on sampled-data and cyber-physical systems. Her work aims to bridge fundamental systems theory and large-scale autonomous robotic coordination.</span></p>
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          <img class="avatar" src="assets/img/speaker/Gennaro_Notomista_2.png" alt="Gennaro Notomista photo">
          <h3>Gennaro Notomista</h3>
          <h1>University of Waterloo</h1>
          <br>
          <p class="talk-title-line"><span class="item-label">Talk Title:</span> <span class="item-text">TBA</span></p>
          <p class="abstract-line"><span class="item-label">Abstract:</span> <span class="item-text">TBA</span></p>
          <p><span class="item-label">Biography:</span> <span class="item-text">Gennaro Notomista is an Assistant Professor and the Varma Family Professor in Robotics in the Department of Electrical and Computer Engineering at the University of Waterloo (Waterloo, ON, Canada). Prior to joining University of Waterloo, he was a post-doctoral researcher at the CNRS/Inria/IRISA, Rennes, France. He received the Ph.D. degree in robotics from the Georgia Institute of Technology (Atlanta, GA, USA) in 2020. Dr. Notomista is a Fulbright Scholar and was the recipient of the Alumni Small Grant (2020) and the IEEE ARSO Best Paper Award (2022). His main research interests lie at the intersection of design and control of robotic systems for long-duration autonomy with applications to environmental monitoring.</span></p>
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