{"id":1050,"date":"2018-09-14T21:00:01","date_gmt":"2018-09-14T21:00:01","guid":{"rendered":"https:\/\/www.aiproblog.com\/index.php\/2018\/09\/14\/connor-coley-named-a-chemical-and-engineering-news-talented-twelve\/"},"modified":"2018-09-14T21:00:01","modified_gmt":"2018-09-14T21:00:01","slug":"connor-coley-named-a-chemical-and-engineering-news-talented-twelve","status":"publish","type":"post","link":"https:\/\/www.aiproblog.com\/index.php\/2018\/09\/14\/connor-coley-named-a-chemical-and-engineering-news-talented-twelve\/","title":{"rendered":"Connor Coley named a Chemical and Engineering News Talented Twelve"},"content":{"rendered":"<p>Author: Melanie Kaufman | Department of Chemical Engineering<\/p>\n<div>\n<p>Connor Coley, currently pursuing his graduate degree in chemical engineering at MIT, has been selected as one of 2018\u2019s \u201cTalented Twelve\u201d by <em>Chemical and Engineering News (C&#038;EN)<\/em>, the weekly magazine of the American Chemical Society. Coley was recognized for his work in \u201creprogramming the way chemists design drugs.\u201d<\/p>\n<p>Currently a member of the Klavs Jensen and William Green research groups, Coley is focused on improving automation and computer assistance in synthesis planning and reaction optimization with medicinal chemistry applications. He is more broadly interested in the design and construction of automated microfluidic platforms for analytics (e.g. kinetic or process understanding) and on-demand synthesis. Coley\u2019s work is an integral part of the new MIT-industry consortium, Machine Learning for Pharmaceutical Discovery and Synthesis.<\/p>\n<p>As described in <em>C&#038;EN<\/em>, \u201cMachine learning aims to create artificial intelligence systems that make decisions with little intervention from people. Coley&#8217;s efforts in this arena have blossomed into a collaboration between MIT and eight drug industry partners, known as the Machine Learning for Pharmaceutical Discovery and\u00a0Synthesis Consortium. While most other chemists working in the field of machine learning and chemical synthesis use rules devised by experts to guide their systems, Coley relies on reactions in databases, such as those in U.S. patent filings, to teach the computer what transformations will and won&#8217;t take place without being influenced by human bias.\u201d<\/p>\n<p>Earlier this year, Coley was also named a 2018 \u201cRiser\u201d by the U.S. Defense Advanced Research Projects Agency (DARPA).<\/p>\n<p>To find its annual Talented Twelve, <em>C&#038;EN<\/em> consulted a panel of industry advisers, the publication&#8217;s advisory board, and Talented Twelve alumni to nominate prospects aged 42 or younger \u201cwho are taking risks in the early stages of their career.\u201d They also accepted nominations from readers through an online form. The team researched and evaluated more than 350 candidates before finalizing the 2018 Talented Twelve.<\/p>\n<p>Professors Brady Olsen and Fikile Brushett, also of MIT Chemical Engineering, have previously been named to this group.<\/p>\n<\/div>\n<p><a href=\"http:\/\/news.mit.edu\/2018\/mit-connor-coley-chemical-engineering-news-talented-twelve-0914\">Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Author: Melanie Kaufman | Department of Chemical Engineering Connor Coley, currently pursuing his graduate degree in chemical engineering at MIT, has been selected as one [&hellip;] <span class=\"read-more-link\"><a class=\"read-more\" href=\"https:\/\/www.aiproblog.com\/index.php\/2018\/09\/14\/connor-coley-named-a-chemical-and-engineering-news-talented-twelve\/\">Read More<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":474,"comment_status":"registered_only","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[24],"tags":[],"_links":{"self":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/1050"}],"collection":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/comments?post=1050"}],"version-history":[{"count":0,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/1050\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media\/461"}],"wp:attachment":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media?parent=1050"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/categories?post=1050"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/tags?post=1050"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}