{"657844":{"#nid":"657844","#data":{"type":"event","title":"ECE Seminar: Trustworthy human-centered machine intelligence for well-being and healthcare","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EDate:\u003C\/strong\u003E\u0026nbsp;Wednesday, May 11, 2022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime: \u003C\/strong\u003E11:00 a.m. - 12:30 p.m.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;TSRB 509\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EVirtual: \u003C\/strong\u003E\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/93602154844?pwd=RTJoSTA5VWJYd2dTci9vOUhEQi9SQT09\u0022\u003EZoom\u003C\/a\u003E -\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003ESee additional\u0026nbsp;instructions below\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Theodora Chaspari\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESpeaker\u0026rsquo;s Title:\u003C\/strong\u003E\u0026nbsp;Assistant Professor,\u0026nbsp;Computer Science \u0026amp; Engineering Department\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESpeaker\u0026rsquo;s Affiliation\u003C\/strong\u003E: Texas A\u0026amp;M University\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESeminar Title:\u0026nbsp;\u003C\/strong\u003ETrustworthy human-centered\u0026nbsp;machine intelligence\u0026nbsp;for\u0026nbsp;well-being and\u0026nbsp;healthcare\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;Recent converging advances in sensing and computing allow the\u0026nbsp;ambulatory\u0026nbsp;long-term tracking of individuals yielding\u0026nbsp;a\u0026nbsp;rich\u0026nbsp;set of real-life\u0026nbsp;multimodal\u0026nbsp;bio-behavioral\u0026nbsp;measurements, such as speech, physiology, and facial expressions. While\u0026nbsp;bio-behavioral\u0026nbsp;measurements\u0026nbsp;coupled with\u0026nbsp;artificial intelligence (AI) and\u0026nbsp;machine learning algorithms\u0026nbsp;have been heralded as promising\u0026nbsp;solutionsto\u0026nbsp;empowering\u0026nbsp;physical and\u0026nbsp;mental healthcare,\u0026nbsp;various confounding factors prevent the widespread adoption of\u0026nbsp;such\u0026nbsp;technologies, including the\u0026nbsp;complex and heterogeneous data spaces, limited\u0026nbsp;numberof labels, and high\u0026nbsp;inter-individual\u0026nbsp;variability. At the same time,\u0026nbsp;interactions between humans and AI\u0026nbsp;are increasingly\u0026nbsp;moving\u0026nbsp;away\u0026nbsp;from simple diagnosis\u0026nbsp;of human outcomes to collaborative relationships, in which humans work side-by-side with AI systems for\u0026nbsp;carrying out a set of common goals.\u0026nbsp;The first part of this\u0026nbsp;talk will present approaches to\u0026nbsp;address computational challenges related to\u0026nbsp;robust\u0026nbsp;human-centered machine\u0026nbsp;learning, including\u0026nbsp;the design of subject- and group-specific machine learning models\u0026nbsp;with emphasis on generalizability to unseen conditions.\u0026nbsp;The second part of the talk will focus on\u0026nbsp;AI-assisted\u0026nbsp;decision making across\u0026nbsp;two\u0026nbsp;main pillars of trustworthiness, namely\u0026nbsp;privacy-preservation\u0026nbsp;and\u0026nbsp;fairness.\u0026nbsp;Specifically,\u0026nbsp;we will\u0026nbsp;present\u0026nbsp;a\u0026nbsp;privacy-preserving emotion\u0026nbsp;recognition\u0026nbsp;framework\u0026nbsp;through user anonymization and discuss factors of socio-demographic bias in AI\u0026nbsp;systems that may\u0026nbsp;perpetuate\u0026nbsp;social disparities.\u0026nbsp;We will demonstrate the effectiveness of the proposed approaches through examples in\u0026nbsp;daily well-being,\u0026nbsp;mental health,\u0026nbsp;communication anxiety, and\u0026nbsp;workforce training\u0026nbsp;and re-skilling.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESpeaker Bio:\u003C\/strong\u003E\u0026nbsp;Theodora Chaspari is an Assistant Professor\u0026nbsp;in\u0026nbsp;the Computer Science \u0026amp; Engineering Department\u0026nbsp;atTexas A\u0026amp;M University. She has received\u0026nbsp;her\u0026nbsp;Bachelor of Science (2010) in Electrical\u0026nbsp;\u0026amp;\u0026nbsp;Computer Engineering from the National Technical University of Athens, Greece and\u0026nbsp;her\u0026nbsp;Master of Science (2012) and Ph.D. (2017) in Electrical Engineering from the University of Southern California. Between 2010\u0026nbsp;and\u0026nbsp;2017 she worked\u0026nbsp;as a Research Assistant at the Signal Analysis and Interpretation Laboratory at USC. She has also been a Lab Associate Intern at Disney Research (2015).\u0026nbsp;Theodora\u0026rsquo;s\u0026nbsp;research interests lie in the areas of\u0026nbsp;signal processing, machine learning, data science,\u0026nbsp;and affective computing.\u0026nbsp;She is a recipient of the\u0026nbsp;TEES Dean of Engineering Excellence Award (2022),\u0026nbsp;TEES Young Faculty Award (2022),\u0026nbsp;NSF CAREER Award (2021), TAMU Montague Teaching\u0026nbsp;Award\u0026nbsp;(2021),\u0026nbsp;USC Women in Science and Engineering Merit Fellowship\u0026nbsp;(2015), and USC Annenberg Graduate Fellowship (2010).\u0026nbsp;Papers co-authored with her students have been nominated and won awards at the\u0026nbsp;ASC 2021,\u0026nbsp;ACM BuildSys 2019, IEEE ACII 2019, ASCE i3CE 2019, and IEEE BSN 2018 conferences. She\u0026nbsp;is serving as an Editor of the Elsevier Computer Speech \u0026amp; Language, and\u0026nbsp;in\u0026nbsp;various\u0026nbsp;conference organization committees (ACM ICMI\u0026nbsp;2023\/2020\/2018, ACM IUI 2021, ACM KDD 2022, IEEE\u0026nbsp;ACII\u0026nbsp;2022\/2021\/2019\/2017, IEEE BSN 2018).Her work is supported by federal and private funding sources, including the\u0026nbsp;NSF, NIH,\u0026nbsp;NASA,\u0026nbsp;IARPA, AFRL,\u0026nbsp;AFOSR, General Motors, Keck Foundation, and the\u0026nbsp;Engineering Information Foundation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EVirtual Meeting information:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoin Zoom Meeting\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/93602154844?pwd=RTJoSTA5VWJYd2dTci9vOUhEQi9SQT09\u0022 title=\u0022https:\/\/gatech.zoom.us\/j\/93602154844?pwd=RTJoSTA5VWJYd2dTci9vOUhEQi9SQT09\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/93602154844?pwd=RTJoSTA5VWJYd2dTci9vOUhEQi9SQT09\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMeeting ID: 936 0215 4844\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPasscode: 117418\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOne tap mobile\u003C\/p\u003E\r\n\r\n\u003Cp\u003E+19292056099,,93602154844#,,,,*117418# US (New York)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E+13017158592,,93602154844#,,,,*117418# US (Washington DC)\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDial by your location\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp; 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