{"674289":{"#nid":"674289","#data":{"type":"news","title":"MSA Team Wins 2023 TAG Master Modeler Competition","body":[{"value":"\u003Cp\u003EBy Shelley Wunder-Smith\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEvery year, the Technology Association of Georgia (TAG) sponsors a multi-stage data science challenge called Master Modelers, in which teams are tasked with solving a social problem using data. In 2023, the top three academic teams were all students from Georgia Tech\u2019s\u0026nbsp;\u003Ca href=\u0022https:\/\/www.analytics.gatech.edu\/node\/1\u0022\u003EMaster of Science in Analytics\u003C\/a\u003E\u0026nbsp;(MSA) program; this included the Abnormal Unsupervised Distribution team \u2014 consisting of\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/rakesh-kumar-arwini-14958312a\/\u0022\u003ERakesh Arwini\u003C\/a\u003E\u0026nbsp;\u003C\/strong\u003E(MSA 23),\u0026nbsp;\u003Ca href=\u0022https:\/\/it.linkedin.com\/in\/cassidy-gasteiger\u0022\u003E\u003Cstrong\u003ECassidy Gasteiger\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;(MSA 23),\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/samaksh-gulati-38b842119\/\u0022\u003E\u003Cstrong\u003ESamaksh Gulati\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;(MSA 23), and\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/sai-sri-harsha-pinninti\/\u0022\u003ESai Sri Harsha Pinninti\u003C\/a\u003E\u0026nbsp;\u003C\/strong\u003E(MSA 23) \u2014 as the overall winner.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EParticipants were asked to use data to provide the\u0026nbsp;\u003Ca href=\u0022https:\/\/www.nchcw.org\u0022\u003ENational Center for Housing and Child Welfare\u003C\/a\u003E\u0026nbsp;(NCHCW) and other related nonprofits with meaningful insights, models, and solutions to make a social impact. The NCHCW is a leading organization that helps provide affordable housing for families on the local, regional, and national level, with the ultimate goal of keeping children out of foster care due to homelessness. The organizers of Master Modelers encouraged the teams to focus on creating useful models rather than innovative ones.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cIn data science, you can build fancy models, but they don\u2019t always go somewhere,\u201d said Gasteiger. \u201cSo in this challenge, it was good to know that even if we built a basic model, it would still be useful.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cThat was an important realization,\u201d Gulati added. \u201cData science isn\u2019t always about building innovative models. Using our skills to help someone make practical decisions is much more important.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe primary objective the Master Modeler teams were asked to solve was identifying the relationship between housing insecurity and children being placed into foster care \u2014 not a small challenge.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cWe had anonymized data for every foster child in the U.S. that showed their reason for removal into foster care and how long they were there, and that was our core dataset,\u201d explained Gasteiger. \u201cWe also had an adoption dataset for children who were adopted out of foster care. The first half of our analysis was focused on understanding how housing insecurity affects removal into foster care.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe team had found a connection between states with high removal rates and difficult housing rental environments. The second stage of their analysis involved actual modeling, through which they could accurately predict whether or not a child would be adopted, as well as if a child would be reunified with their family. The poorer a child is, the less likely they are to be reunited their family.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIt was a sobering discovery, but the hope is that by providing NCHCW with this kind of information, the organization will be equipped to act as effectively as possible.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EScott Reynolds, manager of technology business operations at Synovus, which sponsored the competition, said in\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/posts\/scott-reynolds-csm-75361162_techforgood-synovus-herematters-activity-7047897997380112386-ec2o\/?utm_source=share\u0026amp;utm_medium=member_desktop\u0022\u003Ea LinkedIn post\u003C\/a\u003E\u0026nbsp;after the event, \u201cSynovus was proud to help sponsor the 2023 TAG Master Modeler Competition to benefit the National Center for Housing and Child Welfare.\u0026nbsp;...\u0026nbsp;It was amazing to see how data can be used to help so many children across the U.S.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAs the winners, the\u0026nbsp;Abnormal Unsupervised Distribution team was invited to present their findings at the April 2023 INFORMS Business Analytics Conference in\u0026nbsp;Colorado.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cThis competition was an incredible experience,\u201d Gulati said. \u201cWe learned more about the U.S. foster system and applied data analytics to make recommendations. We welcomed the opportunity to apply what we\u0027ve learned in the MSA program to solve complex community problems.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor more information on the 2024 competition, visit the\u0026nbsp;\u003Ca href=\u0022https:\/\/www.tagonline.org\/societies\/data-science-analytics\/master-modeler-competition\/\u0022\u003ETAG Master Modeler site\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe students created a model that accurately identifies whether a child in foster care will be reunified with their family, which will help guide advocacy for nonprofits working in this area.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The students created a model that accurately identifies whether a child in foster care will be reunified with their family, which will help guide advocacy for nonprofits working in this area."}],"uid":"36359","created_gmt":"2024-04-19 18:59:55","changed_gmt":"2024-05-10 15:34:19","author":"ecalhoun8","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2023-03-25T00:00:00-04:00","iso_date":"2023-03-25T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"673979":{"id":"673979","type":"image","title":"Tagta","body":null,"created":"1715355142","gmt_created":"2024-05-10 15:32:22","changed":"1715355204","gmt_changed":"2024-05-10 15:33:24","alt":"Tag","file":{"fid":"257441","name":"download.jpg","image_path":"\/sites\/default\/files\/2024\/05\/10\/download.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/05\/10\/download.jpg","mime":"image\/jpeg","size":7295,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/05\/10\/download.jpg?itok=ESTnb36M"}}},"media_ids":["673979"],"groups":[{"id":"660346","name":"Master of Science in Analytics"}],"categories":[{"id":"193157","name":"Student Honors and Achievements"}],"keywords":[{"id":"117311","name":"MSA"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}