{"636139":{"#nid":"636139","#data":{"type":"event","title":"Ph.D. Proposal Oral Exam - Hyung Joon Cho","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003EDeep Learning Based Optical Performance Monitoring for Digital Coherent Optical Receivers\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Ralph, Advisor\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Klein, Chair\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Romberg\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThe objectives of the proposed research are (a) to develop machine learning techniques that can estimate optical performance monitoring metrics in optical communication, deploying a new optical link and checking the conditions of the established links; (b) to assess the performance of the associated machine learning techniques; (c) to understand the factors that limit the estimation performance; and (d) to identify optimal proxies for applying machine learning in digital coherent optical receivers.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Deep Learning Based Optical Performance Monitoring for Digital Coherent Optical Receivers"}],"uid":"28475","created_gmt":"2020-06-10 18:13:18","changed_gmt":"2020-06-10 18:13:18","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-06-22T14:00:00-04:00","event_time_end":"2020-06-22T16:00:00-04:00","event_time_end_last":"2020-06-22T16:00:00-04:00","gmt_time_start":"2020-06-22 18:00:00","gmt_time_end":"2020-06-22 20:00:00","gmt_time_end_last":"2020-06-22 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"434371","name":"ECE Ph.D. Proposal Oral Exams"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"},{"id":"1808","name":"graduate students"}],"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":""}}}