{"618024":{"#nid":"618024","#data":{"type":"event","title":"SCS Recruiting Seminar: Yongjoo Park","body":[{"value":"\u003Cp\u003ETITLE: \u003Cem\u003EBringing Statistical Trade-offs to Data Systems\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EABSTRACT:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDespite advances in computing power, the cost of large-scale analytics and machine learning remains daunting to small and large enterprises alike. This has created a pressing demand for reducing infrastructure costs and query latencies. To meet these goals, data analysts and applications are in many cases willing to tolerate a slight \u0026mdash; but controlled \u0026mdash; degradation of accuracy in exchange for substantial gains in cost and performance, which we refer to as statistical trade-offs. This is particularly true in the early stages of data exploration and is in stark contrast to traditional trade-offs where the infrastructure costs must increase for higher performance.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMy research builds large-scale data systems that can make these statistical trade-offs in a principled manner. In this talk, I will focus on two specific directions. First, I will present VerdictDB, a system that enables quality-guaranteed, statistical trade-offs without any changes to backend infrastructure; thus, it offers a universal solution for off-the-shelf query engines. Second, I will introduce Database Learning, a new query execution paradigm that allows existing query engines to constantly learn from their past executions and become \u0026ldquo;smarter\u0026rdquo; over time without any user intervention. I will conclude by briefly discussing other promising directions with emerging workloads beyond SQL, including visualization and machine learning.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBIO:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;Yongjoo Park is a research fellow in computer science and engineering at the University of Michigan, Ann Arbor. His research interest is software systems for fast data analytics and machine learning. He received a Ph.D. from the University of Michigan, advised by Michael Cafarella and Barzan Mozafari. He is a recipient of 2018 ACM SIGMOD Jim Gray Dissertation Award Runner-up, Kwanjeong Ph.D. Fellowship, and Jeongsong Graduate Study Fellowship.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Bringing Statistical Trade-offs to Data Systems"}],"uid":"34541","created_gmt":"2019-02-18 20:58:15","changed_gmt":"2019-03-06 17:03:56","author":"Tess Malone","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-03-14T12:00:00-04:00","event_time_end":"2019-03-14T13:00:00-04:00","event_time_end_last":"2019-03-14T13:00:00-04:00","gmt_time_start":"2019-03-14 16:00:00","gmt_time_end":"2019-03-14 17:00:00","gmt_time_end_last":"2019-03-14 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"618025":{"id":"618025","type":"image","title":"Yongjoo Park","body":null,"created":"1550523521","gmt_created":"2019-02-18 20:58:41","changed":"1550523521","gmt_changed":"2019-02-18 20:58:41","alt":"Yongjoo Park","file":{"fid":"235255","name":"yongjoo 2018 square.jpg","image_path":"\/sites\/default\/files\/images\/yongjoo%202018%20square.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/yongjoo%202018%20square.jpg","mime":"image\/jpeg","size":905958,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/yongjoo%202018%20square.jpg?itok=zS35rH6h"}}},"media_ids":["618025"],"groups":[{"id":"50875","name":"School of Computer Science"},{"id":"47223","name":"College of Computing"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"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":[{"value":"\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cp\u003ETess Malone, Communications Officer\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022mailto:tess.malone@cc.gatech.edu\u0022\u003Etess.malone@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}