{"674645":{"#nid":"674645","#data":{"type":"event","title":"PhD Defense by Yingke Li","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EBayesian Learning: Paving to Way to Trustworthy Robots\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate:\u0026nbsp;\u003C\/strong\u003EFriday, May 24, 2024\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime:\u0026nbsp;\u003C\/strong\u003E11:00AM \u2013 1:00PM\u0026nbsp;EDT\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation:\u0026nbsp;\u003C\/strong\u003E\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_NjM5MDY3NjItYWU5Yi00YTRjLWI1NTEtY2Y4NDVhMTYwNDg4%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22127397ee-6044-4700-8f48-28f202a64df4%22%7d\u0022 title=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_MWNiYWVkZWYtMTE1YS00NGI5LTk3NTAtZjNkZTg2NDYzODY1%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22127397ee-6044-4700-8f48-28f202a64df4%22%7d\u0022\u003ETeams Meeting\u003C\/a\u003E\u0026nbsp;(Meeting ID: 247 204 698 775 Passcode: CKj5bt)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EYingke Li\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERobotics\u0026nbsp;PhD\u0026nbsp;Candidate\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Electrical and Computer Engineering\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Fumin Zhang (Advisor) \u2013 School of\u0026nbsp;Electrical and Computer Engineering, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Enlu Zhou \u2013\u0026nbsp;School of Industrial and Systems Engineering, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr.\u0026nbsp;Matthieu Bloch\u0026nbsp;\u2013 School of Electrical and Computer Engineering, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr.\u0026nbsp;Seth Hutchinson\u0026nbsp;\u2013 School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Diyi Yang \u2013 Computer Science Department, Stanford University\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOperating under challenging real-world scenarios requires robots to possess a level of \u201ctrustworthiness\u201d, enabling them to interact effectively with complex environments and autonomously execute tasks with minimal human intervention. However, factors such as noisy observations, dynamic environmental conditions, ambiguous human instructions, and evolving human-robot team structures render any deterministic approaches fragile over extended real-world operations. This thesis aims to establish the trustworthiness of robots through a probabilistic lens, more specifically, paving the way to trustworthy robots with Bayesian learning. As an embodiment of common sense reasoning, Bayesian learning provides a formal and consistent way to reasoning in the presence of uncertainty, which empowers robots to address a variety of uncertainties encountered when they navigate in unknown, unstructured, and dynamic environments, especially with the presence of human partners. However, while promising and intuitive, integrating Bayesian learning into robotic techniques poses significant challenges. As such, this dissertation centers on seamlessly incorporating Bayesian learning into various robotic techniques by rigorously addressing the associated challenges in \u003Cem\u003Einference\u003C\/em\u003E and \u003Cem\u003Eaction\u003C\/em\u003E, culminating in a harmonious framework that advances the development of trustworthy robots in real-world scenarios.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EBayesian Learning: Paving to Way to Trustworthy Robots\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Bayesian Learning: Paving to Way to Trustworthy Robots"}],"uid":"27707","created_gmt":"2024-05-10 20:09:36","changed_gmt":"2024-05-10 20:10:12","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-05-24T11:00:55-04:00","event_time_end":"2024-05-24T13:00:55-04:00","event_time_end_last":"2024-05-24T13:00:55-04:00","gmt_time_start":"2024-05-24 15:00:55","gmt_time_end":"2024-05-24 17:00:55","gmt_time_end_last":"2024-05-24 17:00:55","rrule":null,"timezone":"America\/New_York"},"location":"Teams Meeting (Meeting ID: 247 204 698 775 Passcode: CKj5bt)","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}