{"id":1100829,"date":"2024-11-18T07:19:00","date_gmt":"2024-11-18T15:19:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2025-03-24T23:03:53","modified_gmt":"2025-03-25T06:03:53","slug":"microsoft-research-asia-tokyo","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/group\/microsoft-research-asia-tokyo\/","title":{"rendered":"Microsoft Research Asia \u2013 Tokyo"},"content":{"rendered":"<section class=\"mb-3 moray-highlight\">\n\t<div class=\"card-img-overlay mx-lg-0\">\n\t\t<div class=\"card-background  has-background-purple card-background--full-bleed\">\n\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"2560\" height=\"1440\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-scaled.jpg\" class=\"attachment-full size-full\" alt=\"chart, surface chart\" style=\"object-position: 50% 17%\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-scaled.jpg 2560w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-300x169.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-1024x576.jpg 1024w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-768x432.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-1536x864.jpg 1536w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-2048x1152.jpg 2048w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-1066x600.jpg 1066w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-655x368.jpg 655w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-240x135.jpg 240w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-640x360.jpg 640w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-960x540.jpg 960w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-1280x720.jpg 1280w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/11\/msr-asia-tokyo-banner-no-logo-1920x1080.jpg 1920w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/>\t\t<\/div>\n\t\t<!-- Foreground -->\n\t\t<div class=\"card-foreground d-flex mt-md-n5 my-lg-5 px-g px-lg-0\">\n\t\t\t<!-- Container -->\n\t\t\t<div class=\"container d-flex mt-md-n5 my-lg-5 \">\n\t\t\t\t<!-- Card wrapper -->\n\t\t\t\t<div class=\"w-100 w-lg-col-5\">\n\t\t\t\t\t<!-- Card -->\n\t\t\t\t\t<div class=\"card material-md-card py-5 px-md-5\">\n\t\t\t\t\t\t<div class=\"card-body \">\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<h2 class=\"wp-block-heading\" id=\"microsoft-research-asia-tokyo\">Microsoft Research Asia \u2013 Tokyo<\/h2>\n\n\n\n<p><\/p>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n<p>Microsoft is reinforcing its commitment to advancing AI research and innovation across the Asia-Pacific region with the opening of Microsoft Research Asia \u2013 Tokyo. The Tokyo lab will focus on critical areas that reflect Japan&#8217;s socioeconomic priorities, including embodied AI, well-being and neuroscience, societal AI, and industry innovation. These research efforts aim to leverage advanced technologies to foster societal progress and contribute to the region\u2019s innovation ecosystem.<\/p>\n\n\n\n<p>As the fundamental research arm of Microsoft in the Asia-Pacific region, Microsoft Research Asia has a long-standing collaboration with Japan, which began in 2005. The establishment of the Tokyo lab will enhance Microsoft Research Asia\u2019s ability to forge deeper collaborations with local partners, enabling cross-cultural and interdisciplinary exchanges that promote technological advancements.<\/p>\n\n\n\n<p>Our current key focus and initiatives includes:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Embodied AI<\/strong>: Developing intelligent systems that can perform complex tasks and understand and interact in physical and virtual environments.<\/li>\n\n\n\n<li><strong>Societal AI<\/strong>: Exploring the implications of AI on society, ensuring that technology serves humanity&#8217;s best interests.<\/li>\n\n\n\n<li><strong>Well-being and n<\/strong><strong>euroscience:<\/strong> Drawing inspiration from neuroscience to re-imagine human-AI interfaces, applying AI to enhance well-being.<\/li>\n\n\n\n<li><strong>Industry innovation<\/strong>: Embracing interdisciplinary and cross-boundary research to understand real-world needs, empowering industry transformation in collaboration with industry partners.<\/li>\n<\/ul>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n\n\n<p>Tokyo Talk Series is an initiative designed to foster intellectual exchange and collaboration within our research community. This series brings prominent speakers to Microsoft Research Asia &#8211; Tokyo to share their ideas and experiences. The talks will be scheduled on an ad-hoc basis, allowing flexibility to accommodate the availability of our guest speakers.<\/p>\n\n\n\n<p><strong>April 1, 2025:\u00a0From Automation to Autonomy: Machine Learning for Next-generation Robotics<\/strong><\/p>\n\n\n\n<p><strong>Speaker:<\/strong> Professor Sethu Vijayakumar FRSE, The University of Edinburgh, UK<\/p>\n\n\n\n\n\n<p><strong>Abstract:<\/strong><\/p>\n\n\n\n<p>The new generation of robots work much more closely with humans, other robots and interact significantly with the environment around it. As a result, the key paradigms are shifting from isolated decision making systems to one that involves shared control &#8212; with significant autonomy devolved to the robot platform; and end-users in the loop making only high level decisions.<\/p>\n\n\n\n<p>This talk will briefly introduce powerful machine learning technologies ranging from robust multi-modal sensing, shared representations, scalable real-time learning and adaptation, and compliant actuation that are enabling us to reap the benefits of increased autonomy while still feeling securely in control.<\/p>\n\n\n\n<p>This also raises some fundamental questions: while the robots are ready to share control, what is the optimal trade-off between autonomy and control that we are comfortable with?<\/p>\n\n\n\n<p>Domains where this debate is relevant include deployment of robots in extreme environments, self-driving cars, asset inspection, repair & maintenance, factories of the future and assisted living technologies including exoskeletons and prosthetics to list a few.<\/p>\n\n\n\n<p><strong>Bio:<\/strong><\/p>\n\n\n\n<p>Sethu Vijayakumar is the Professor of Robotics at the University of Edinburgh, UK and the Founding Director of the Edinburgh Centre for Robotics.&nbsp; He has pioneered the use of large-scale machine learning techniques in the real-time control of several iconic robotic platforms such as the SARCOS and the HONDA ASIMO humanoids, KUKA-LWR robot arm and iLIMB prosthetic hand. He had held adjunct faculty positions at the University of Southern California (USC), Los Angeles and the RIKEN Brain Science Institute, Japan. One of his landmark projects (2016) involved a collaboration with NASA Johnson Space Centre on the Valkyrie humanoid robot being prepared for unmanned robotic pre-deployment missions to Mars. Professor Vijayakumar, who has a PhD from the Tokyo Institute of Technology, holds the Royal Academy of Engineering (RAEng) &#8211; Microsoft Research Chair at Edinburgh. He has published over 250 peer reviewed and highly cited articles [H-index 50, Citations > 13,000 as of 2025] on topics covering robot learning, optimal control, and real-time planning in high dimensional sensorimotor systems. He is a Fellow of the Royal Society of Edinburgh, a judge on BBC Robot Wars and winner of the 2015 Tam Dalyell Prize for excellence in engaging the public with science. Professor Vijayakumar helps shape and drive the UK Robotics and Autonomous Systems (RAS) agenda in his recent role as the Programme Director for Robotics and Human AI Interfaces at The Alan Turing Institute, the UK\u2019s national institute for data science and AI.<\/p>\n\n\n\n<p>Sethu also serves as Senior Independent Director (SID) on the Japan Small Caps fund with Baillie Gifford Investment and has been advisor to several UK-Japan Governmental research initiatives for the Japan Ministry of Finance as well as the Ministry of Economy, Trade and Industry.<\/p>\n\n\n\n<p>Webpage: <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/web.inf.ed.ac.uk\/slmc\">https:\/\/web.inf.ed.ac.uk\/slmc<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/p>\n\n\n\n<p>LinkedIn: <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.linkedin.com\/in\/sethu-vijayakumar\">https:\/\/www.linkedin.com\/in\/sethu-vijayakumar<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/p>\n\n\n\n\n\n<p><strong>April 1, 2025:\u00a0Contact-rich and Whole-body Manipulation<\/strong><\/p>\n\n\n\n<p><strong>Speaker:<\/strong> Dr. Jo\u00e3o Moura, Senior Researcher, The University of Edinburgh, UK<\/p>\n\n\n\n\n\n<p><strong>Abstract:<\/strong><\/p>\n\n\n\n<p>Contact-rich manipulation, which involves intricate contact and force interactions with the environment, is crucial for enabling dexterous robotic capabilities. Non-prehensile manipulation tasks, such as pushing or catching objects, present unique challenges due to under-actuation, hybrid dynamics, and model uncertainty. This talk will explore both model-based trajectory optimization and model-free reinforcement learning approaches for addressing these challenges. Furthermore, whole-body manipulation can significantly enhance a robot\u2019s reachability and mobility. However, the increased degrees of freedom and multiple contact points introduce additional complexities, including high-dimensionality and nonlinear dynamics. Advancing contact-rich whole-body manipulation holds great potential across various domains, from nuclear decommissioning and assistive healthcare to enhancing robots\u2019 ability to support daily-life activities.<\/p>\n\n\n\n<p><strong>Bio:<\/strong><\/p>\n\n\n\n<p>Jo\u00e3o Moura is a senior researcher at The University of Edinburgh, UK, and a research fellow at the Robotics and AI Collaboration (RAICo) in Whitehaven, UK. He earned his PhD (2021) and MSc by Research (with distinction, 2016) in Robotics and Autonomous Systems, jointly awarded by Heriot-Watt University and The University of Edinburgh, UK. He also holds a diploma degree (BSc + MSc, 2012) in Mechanical Engineering from the University of Aveiro, Portugal, where he graduated top of his cohort. Before pursuing PhD, Jo\u00e3o worked as a research assistant at INESC TEC Porto\u2019s Centre for Robotics and Intelligent Systems, contributing to the FP7 European Project ICARUS\u2014Integrated Components for Assisted Rescue and Unmanned Search operations. He also served as a teaching assistant at the University of Aveiro, lecturing courses in robotics, control systems, and programming. Currently, he collaborates with Waseda University as part of Goal 3 of Japan\u2019s Moonshot programme. Previously, he participated in the H2020 European Project Harmony\u2014Enhancing Healthcare with Assistive Robotic Mobile Manipulation. Jo\u00e3o has published in the top-tier robotics conferences and journals, including IROS, ICRA, CoRL, R:SS, RA-L, IJRR, and T-RO, having received nominations for Best Student Paper Award and Best Paper Award at the R:SS conference. His research focuses on trajectory optimization (TO), model predictive control (MPC), learning from demonstration (LfD), and reinforcement learning (RL) for contact-rich and non-prehensile manipulation.<\/p>\n\n\n\n<p>Webpage: <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/sites.google.com\/view\/joaomoura\">https:\/\/sites.google.com\/view\/joaomoura<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/p>\n\n\n\n<p>LinkedIn: <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.linkedin.com\/in\/joaopousamoura\">https:\/\/www.linkedin.com\/in\/joaopousamoura<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/p>\n\n\n\n\n\n<p><\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>Microsoft is reinforcing its commitment to advancing AI research and innovation across the Asia-Pacific region with the opening of Microsoft Research Asia \u2013 Tokyo. The Tokyo lab will focus on critical areas that reflect Japan&#8217;s socioeconomic priorities, including embodied AI, well-being and neuroscience, societal AI, and industry innovation. These research efforts aim to leverage advanced [&hellip;]<\/p>\n","protected":false},"featured_media":1103664,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_group_start":"","footnotes":""},"research-area":[13556,13554],"msr-group-type":[243694],"msr-locale":[268875],"msr-impact-theme":[],"class_list":["post-1100829","msr-group","type-msr-group","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-computer-interaction","msr-group-type-group","msr-locale-en_us"],"msr_group_start":"","msr_detailed_description":"","msr_further_details":"","msr_hero_images":[],"msr_research_lab":[199560,1012650],"related-researchers":[{"type":"user_nicename","display_name":"Yasuyuki Matsushita","user_id":43707,"people_section":"Section name 0","alias":"yamatsushita"}],"related-publications":[],"related-downloads":[],"related-videos":[],"related-projects":[],"related-events":[],"related-opportunities":[],"related-posts":[1054791,1104399],"tab-content":[],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/1100829","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-group"}],"version-history":[{"count":22,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/1100829\/revisions"}],"predecessor-version":[{"id":1135168,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/1100829\/revisions\/1135168"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/1103664"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1100829"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1100829"},{"taxonomy":"msr-group-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group-type?post=1100829"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1100829"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1100829"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}