{"619479":{"#nid":"619479","#data":{"type":"event","title":"SCS Recruiting Seminar: Anand Iyer","body":[{"value":"\u003Cp\u003ETITLE: \u003Cem\u003EScalable Systems for Large-Scale Dynamic Connected Data Processing\u003C\/em\u003E\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EASBTRACT:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAs the proliferation of sensors rapidly make the Internet-of-Things (IoT) a reality, the devices and sensors in this ecosystem \u0026mdash;such as smartphones, video cameras, home automation systems, and autonomous vehicles \u0026mdash; constantly map out the real-world producing unprecedented amounts of connected data that captures complex and diverse relations. Unfortunately, existing big data processing and machine learning frameworks are ill-suited for analyzing such dynamic connected data and face several challenges when employed for this purpose.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\nIn this talk, I will present my research that focuses on building scalable systems for dynamic connected data processing. I will discuss simple abstractions that make it easy to operate on such data, efficient data structures for state management, and computation models that reduce redundant work. I will also describe how bridging theory and practice with algorithms and techniques that leverage approximation and streaming theory can significantly speed up computations. The systems I have built achieve more than an order of magnitude improvement over the state-of-the-art and are currently under evaluation in the industry for real-world deployments. I will end the talk with my vision for building the next generation data intensive systems that incorporates both the cloud and the edge.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBIO:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnand Iyer is a Ph.D. candidate at the University of California, Berkeley advised by Professor Ion Stoica. His research interests are in cloud computing, systems for big data analytics, and mobile systems with a current focus on enabling efficient analysis and machine learning on large-scale dynamic, connected data. He is a recipient of the best paper award at SIGMOD GRADES-NDA 2018 for his work on approximate graph analytics. Before coming to Berkeley, he was a member of the mobility, networking, and systems group at Microsoft Research India. He completed his M.S at the University of Texas at Austin. \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":"Scalable Systems for Large-Scale Dynamic Connected Data Processing  "}],"uid":"34541","created_gmt":"2019-03-21 17:29:04","changed_gmt":"2019-03-21 17:30:48","author":"Tess Malone","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-04-04T12:00:00-04:00","event_time_end":"2019-04-04T13:00:00-04:00","event_time_end_last":"2019-04-04T13:00:00-04:00","gmt_time_start":"2019-04-04 16:00:00","gmt_time_end":"2019-04-04 17:00:00","gmt_time_end_last":"2019-04-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"619480":{"id":"619480","type":"image","title":"Anand Iyer","body":null,"created":"1553189367","gmt_created":"2019-03-21 17:29:27","changed":"1553189367","gmt_changed":"2019-03-21 17:29:27","alt":"Anand Iyer","file":{"fid":"235849","name":"Anand_Headshot2.jpg","image_path":"\/sites\/default\/files\/images\/Anand_Headshot2.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/Anand_Headshot2.jpg","mime":"image\/jpeg","size":2039268,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/Anand_Headshot2.jpg?itok=WdFGZd-y"}}},"media_ids":["619480"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"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\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\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}