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        "event_title":"MLK Leadership Seminar Series: Leadership for Democracy & Justice",
        "occurrence_title":"CANCELLED - Red Pill or Blue Pill?: The Decision making process within a democracy",
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        "description":"Presented by the Office of Graduate and Postdoctoral Studies, we invite you to the Medical School's MLK Leadership Seminar Series to honor the life, legacy, and leadership of Rev. Dr. Martin Luther King, Jr.The theme for this year's series is \"Leadership for Democracy and Justice,\" a vital pillar of this year\u2019s campus symposium theme:\u00a0\"Unbowed and Unbroken: The Enduring Struggle for Justice.\"\u00a0(https:\/\/oami.umich.edu\/mlk-symposium\/)Running for six sessions from the MLK holiday through the end of Black History Month, this series bridges the gap between leadership scholarship and the urgent understandings required to navigate our modern political landscape.\u00a0Participants will gain the essential tools and theoretical foundations needed to challenge the status quo and lead with purpose in today's society.\u00a0Don\u2019t miss this opportunity to transform your influence into a powerful force for democratic progress and social equity\u2014register today to help solve the equation for a more just world.",
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        "event_title":"Multi-modal Representation Learning for Contact-rich and Dexterous Manipulation",
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        "combined_title":"Multi-modal Representation Learning for Contact-rich and Dexterous Manipulation: Robotics PhD Defense, Youngsun Wi",
        "event_subtitle":"Robotics PhD Defense, Youngsun Wi",
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        "description":"Co-Chairs: Dmitry Berenson and Nima Fazeli\n\nAbstract:\nMy PhD research focuses on representation learning with force and touch for contact rich, dexterous robot manipulation. Recent robot learning has made major progress in vision and language, but those modalities alone cannot fully capture physical interaction in robot manipulation tasks. Tasks like cleaning, assembly, and assistive care require robots to reason about contact and force, especially in the presence of sensor noise and visual occlusion. My work develops learning based methods that integrate force and tactile sensing into robot learning and control. I build object centric multi-modal (vision and touch) representations to infer object state and contact under noise and occlusion, design contact aware planning and control frameworks with learned dynamics to regulate interaction that effectively integrated with language modality, and develop shared tactile representations that align human and robot touch signals for cross embodiment policy transfer. Overall, this dissertation studies how force, touch, and contact can improve robotic dexterity in contact rich manipulation.\n\nZoom:\nhttps:\/\/umich.zoom.us\/j\/95094568449\nMeeting ID: 950 9456 8449\nPasscode: 837399",
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