{"613667":{"#nid":"613667","#data":{"type":"news","title":"Georgia Tech Ph.D. Student Wins Best Paper Honorable Mention at VISxAI 2018","body":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.cse.gatech.edu\/\u0022\u003EGeorgia Tech Computational Science and Engineering (CSE)\u003C\/a\u003E Ph.D. student \u003Cstrong\u003EFred Hohman\u003C\/strong\u003E was recently recognized with an honorable mention for best paper at this year\u0026rsquo;s\u0026nbsp;VISxAI workshop. The workshop is a part of the\u0026nbsp;\u003Ca href=\u0022http:\/\/ieeevis.org\/year\/2018\/welcome\u0022\u003EIEEE VIS 2018\u003C\/a\u003E conference.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHohman\u0026rsquo;s \u0026ldquo;explorable\u0026rdquo; article \u003Ca href=\u0022https:\/\/idyll.pub\/post\/dimensionality-reduction-293e465c2a3443e8941b016d\/\u0022\u003EThe Beginner\u0026rsquo;s Guide to Dimensionality\u003C\/a\u003E Reduction was created in collaboration with \u003Cstrong\u003EMatt Conlen\u003C\/strong\u003E of the University of Washington. Using a dataset of artworks from the Metropolitan Museum of Art in New York City, Hohman and Conlen explore the methods that data scientists use to visualize high-dimensional data.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisualizing the myriad connections between all of the different features of each artwork in a high-dimensional graph could provide new insights. However, as Hohman says in the article, humans can\u0026rsquo;t see so many dimensions all at once.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDimensionality reduction algorithms reduce the number of random variables by collecting a set of principal variables that retain the variation present in the data. This allows the data to be presented in fewer dimensions, which can be more easily processed by human viewers. This kind of projection is called an\u0026nbsp;\u003Cem\u003Eembedding\u003C\/em\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe guide teaches users about embeddings and compares some of the most popular dimensionality reduction algorithms used today to create them. The article also contains a list of pros and cons for each of the algorithms to help readers use this technique for their own data. All of the algorithms mentioned are open-source Python implementations.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026ldquo;Explorable and interactive articles are a great medium for teaching concepts that haven\u0026rsquo;t seen much usage and attention in academia yet,\u0026rdquo; said Hohman. \u0026ldquo;It\u0026rsquo;s really great to see recognition for our article, which helps people learn and engage with complicated concepts through interactive visualizations that are easily accessible on the web,\u0026rdquo; said Hohman.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIEEE VIS is the flagship conference on visualization and visual analytics. Hohman was also a panelist at this year\u0026rsquo;s event, and his advisor, CSE Associate Professor \u003Cstrong\u003EPolo Chau\u003C\/strong\u003E, served as a co-organizer of VISxAI. IEEE VIS was held Oct. 21-26 in Berlin, Germany.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor more information on Georgia Tech\u0026rsquo;s presence at IEEE VIS, explore highlights with the \u003Ca href=\u0022https:\/\/gvu.gatech.edu\/vis-2018\u0022\u003EGVU Center\u0026rsquo;s interactive overview.\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Hohman and Conlen demonstrate how artwork from the Metropolitan Museum of Art can be categorized using machine learning techniques."}],"uid":"34773","created_gmt":"2018-11-01 19:44:23","changed_gmt":"2018-12-03 17:19:59","author":"ablinder6","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2018-11-01T00:00:00-04:00","iso_date":"2018-11-01T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"613693":{"id":"613693","type":"image","title":"ML@GT Ph.D. student Fred Hohman collaborated with Matt Conlen of the University of Washington to create an explorable paper about high-dimensional data visualization.","body":null,"created":"1541105775","gmt_created":"2018-11-01 20:56:15","changed":"1541605649","gmt_changed":"2018-11-07 15:47:29","alt":"","file":{"fid":"233722","name":"me6-1 copy.jpg","image_path":"\/sites\/default\/files\/images\/me6-1%20copy.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/me6-1%20copy.jpg","mime":"image\/jpeg","size":292177,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/me6-1%20copy.jpg?itok=pwFLfWju"}}},"media_ids":["613693"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"576481","name":"ML@GT"},{"id":"50877","name":"School of Computational Science and Engineering"},{"id":"1299","name":"GVU Center"}],"categories":[],"keywords":[],"core_research_areas":[{"id":"39501","name":"People and Technology"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EAllie McFadden\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECommunications Officer\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eallie.mcfadden@cc.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}