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Copy file name to clipboardExpand all lines: app/(default)/(event)/rss2026/workshop/schedule.tsx
+11-24Lines changed: 11 additions & 24 deletions
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@@ -81,20 +81,22 @@ const scheduleItems: {
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bilibili: "",
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},
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slides: "",
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bio: "Tianyu Li is the co-founder of Archon Robotics and a PhD researcher affiliated with Fudan University, Shanghai Innovation Institute, and OpenDriveLab. His research focuses on Physical AI, autonomous driving, end-to-end autonomous driving systems, 3D reconstruction, and generative models.",
bio: "Yi Li is an Assistant Professor in the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University. He received his PhD from Stanford University advised by Leonidas J. Guibas, and later worked as a Research Scientist at Google. His recent research interests include 3D perception, humanoid robot learning, and human-robot interaction.",
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},
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{
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type: "talk",
@@ -124,17 +126,17 @@ const scheduleItems: {
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{
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type: "talk",
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time: "10:30 AM",
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name: "Shan Luo",
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nameLink: "https://shanluo.github.io/",
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affiliation: "King's College London, UK",
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affiliationLogo: "/assets/brand/kcl.png",
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name: "Marcel Torne",
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nameLink: "https://marceltorne.github.io/",
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affiliation: "Stanford, Physical Intelligence",
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affiliationLogo: "/assets/brand/stanford.png",
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title: "TBD",
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recordings: {
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youtube: "",
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bilibili: "",
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},
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slides: "",
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bio: "Shan Luo is currently a Reader in Robotics and AI at the Department of Engineering, King's College London, where he leads the Robot Perception Lab (RPL). He is an enthusiastic and dedicated researcher doing research on robot perception with vision and tactile sensing, leveraging machine learning and computer vision algorithms with applications in robotics, e.g., robot perception, object recognition & localisation, and multimodal sensing fusion. He was a Lecturer (Assistant Professor) at the Department of Computer Science, the University of Liverpool, from 2018 to 2021, and was Director for the smARTLab at the Department. Prior to that, he was a Postdoctoral Research Fellow at Harvard University from 2017 to 2018, and at the University of Leeds from 2016 to 2017. He received the PhD degree in Robotics from King's College London, in 2016. He was a Visiting Scientist at the Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT, in 2016. He is a Fellow of the Higher Education Academy (FHEA).",
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bio: "Marcel Torne is a researcher at Stanford and Physical Intelligence. His research focuses on learning-based assistive robots and methods for in-context adaptation of policies to unseen scenarios with an emphasis on human-centric approaches.",
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},
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{
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type: "talk",
@@ -151,21 +153,6 @@ const scheduleItems: {
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slides: "",
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bio: "Fan Shi is an Assistant Professor at the National University of Singapore, where he holds the prestigious NUS Presidential Young Professorship. His research lies at the intersection of artificial intelligence and robotics, with a focus on physical simulation, robot learning, and the development of scalable methods for embodied intelligence. His work has been recognized through awards and support from leading organizations, including the NVIDIA Academic Grant Program, Google Research, and the Swiss AI Initiative.",
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},
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{
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type: "talk",
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time: "11:30 AM",
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name: "Hamidreza Kasaei",
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nameLink: "https://hkasaei.github.io/",
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affiliation: "University of Groningen, Netherlands",
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affiliationLogo: "/assets/brand/ug.png",
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title: "TBD",
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recordings: {
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youtube: "",
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bilibili: "",
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},
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slides: "",
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bio: "Hamidreza Kasaei is an Associate Professor in the Department of Artificial Intelligence at the University of Groningen, the Netherlands. He has an extensive background in computer vision, machine learning, and robotics. His main research interests lie in the area of 3D Object Perception and Object Manipulation. These days, he is particularly interested in enabling robots to incrementally learn from past experiences and intelligently and safely interact with non-expert human users using data-efficient open-ended machine-learning techniques. Therefore, his research group focuses on Lifelong Interactive Robot Learning (IRL-Lab), which we work at the cutting edge of robotics research.",
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