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Autonomous systems, such as robots and self-driving cars, have rapidly evolved over the past decades. Despite this, several problems remain. Attempts have been made to develop more capable autonomous systems, such as integrating foundation models and utilizing large-scale data. However, the challenging problems have yet to be solved. The motivation behind this workshop is to explore potential solutions, and discuss the challenges and opportunities associated with these approaches. We believe that this workshop serves as a brand-new perspective on the present and future of autonomous systems, and is necessary for both the robotics and computer vision communities.
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<p>June 11</p>
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<ahref="https://maps.app.goo.gl/7YSynr8ff8pVyF1b6" target="_blank" style="text-decoration: underline;">Grand B1, June 11</a>
Yilun Du is currently a senior research scientist at Google Deepmind and an incoming Assistant Professor at Harvard starting in Fall 2025 in the Kempner Institute and CS. He received my PhD at MIT EECS, advised by Prof. Leslie Kaelbling, Prof. Tomas Lozano-Perez and Prof. Joshua B. Tenenbaum. Previously, he also obtained his bachelor's degree from MIT, was a research fellow at OpenAI, an intern and visiting researcher at FAIR and Google Deepmind, and got a gold medal at the International Biology Olympiad. His research focuses on generative models, decision making, robot learning, embodied agents, and the applications of such tools to scientific domains.
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