{"614368":{"#nid":"614368","#data":{"type":"event","title":"Ph.D. Proposal Oral Exam - Shaojie Xu","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003EMACHINE LEARNING ALGORITHM DESIGN FOR HARDWARE PERFORMANCE OPTIMIZATION\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. Romberg, Advisor\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Raychowdhury, Chair\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Wang\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe objective of the proposed research is to combine theory in machine learning, signal processing, and system control for hardware performance optimization. By leveraging collected data to construct a better model for the environment and for specific tasks, machine learning enables the hardware to operate more power-efficiently, to obtain improved results, and to stay robust against environmental changes. The proposed work target three aims: (i) design machine learning algorithms that work with compressively sensed data; (ii) exploit machine learning to improve the speed and the quality of compressive sensing recovery; and (iii) design an adaptive control algorithm for efficient transmitter power amplifier linearization.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"MACHINE LEARNING ALGORITHM DESIGN FOR HARDWARE PERFORMANCE OPTIMIZATION"}],"uid":"28475","created_gmt":"2018-11-16 23:47:47","changed_gmt":"2018-11-16 23:47:47","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-12-04T14:30:00-05:00","event_time_end":"2018-12-04T16:30:00-05:00","event_time_end_last":"2018-12-04T16:30:00-05:00","gmt_time_start":"2018-12-04 19:30:00","gmt_time_end":"2018-12-04 21:30:00","gmt_time_end_last":"2018-12-04 21:30:00","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":""}}}