{"653378":{"#nid":"653378","#data":{"type":"event","title":"PhD Proposal by Sungtae An","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: Weakly Supervised Deep learning for Human Activity Recognition\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESungtae An\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPh.D. Student in Computer Science\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Interactive Computing\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\u003EDate\u003C\/strong\u003E: Thursday, December 9, 2021\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime\u003C\/strong\u003E: 2:00 PM - 4:00 PM EST\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation(Remote via BlueJeans)\u003C\/strong\u003E: \u003Ca href=\u0022https:\/\/bluejeans.com\/190340851\/5419\u0022\u003Ehttps:\/\/bluejeans.com\/190340851\/5419\u003C\/a\u003E\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. Omer T. Inan (Advisor), School of Electrical and Computer Engineering, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. James Rehg (Co-advisor), School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Thomas Ploetz, School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Jon Duke, School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Mindy L. Millard-Stafford, School of Biological Sciences, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Alessio Medda, Aerospace, Transportation \u0026amp; Advanced Systems Laboratory, Georgia Tech Research Institute\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHuman activity recognition (HAR) using wearable sensors and machine learning algorithms is an emerging capability in domains including but not limited to healthcare and ergometric analysis of populations by providing context to physiological measures from wearable sensors during natural daily living activities.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDespite the success of deep supervised models in recent years, obtaining a fully labeled HAR dataset is often difficult due to the high cost and workforce associated with labeling.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnother critical challenge that has often been underestimated is to learn a robust HAR model with noisy training data.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI address these challenges in this dissertation research work with the following contributions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFirst, I present the bilateral domain adaptation problem in HAR for the first time and propose AdaptNet, a semi-supervised deep translation network, which enables information fusion of two different data domains using both unlabeled and labeled data.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENext, I propose a novel framework DynaLAP-VAE, a semi-supervised variational autoencoder with dynamic latent state-space and dynamic prior distribution, which implicitly exploits the information about the environment to enhance HAR in fixed protocols such as military and athletic training with few labeled subject data.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThen, I propose a supervised contrastive learning method with stochastic embeddings to enable the data uncertainty measurement in HAR problems.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Weakly Supervised Deep learning for Human Activity Recognition"}],"uid":"27707","created_gmt":"2021-12-03 19:52:50","changed_gmt":"2021-12-03 19:52:50","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-12-09T14:00:00-05:00","event_time_end":"2021-12-09T16:00:00-05:00","event_time_end_last":"2021-12-09T16:00:00-05:00","gmt_time_start":"2021-12-09 19:00:00","gmt_time_end":"2021-12-09 21:00:00","gmt_time_end_last":"2021-12-09 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}