{"id":2479,"date":"2018-06-06T10:07:26","date_gmt":"2018-06-06T15:07:26","guid":{"rendered":"http:\/\/hachmannlab.cbe.buffalo.edu\/?p=2479"},"modified":"2018-06-06T15:32:06","modified_gmt":"2018-06-06T20:32:06","slug":"atif-mojtaba-and-johannes-at-mlse-2018","status":"publish","type":"post","link":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/atif-mojtaba-and-johannes-at-mlse-2018\/","title":{"rendered":"Atif, Mojtaba, and Johannes at MLSE 2018"},"content":{"rendered":"<p style=\"text-align: justify;\">\n<a href=\"\/index.php\/team\/graduate-students\/atif-faiz\/\">Atif<\/a>, <a href=\"\/index.php\/team\/graduate-students\/mojtaba-haghighatlari\/\">Mojtaba<\/a>, and <a href=\"\/index.php\/team\/johannes-hachmann\/\">Johannes<\/a> are in Pittsburgh (PA) this week for <a title=\"MLSE 2018\" href=\"https:\/\/events.mcs.cmu.edu\/mlse\/\" target=\"_blank\"> Machine Learning in Science and Engineering 2018<\/a>. Mojtaba will present a poster on Wednesday titled &#8220;<i>Software Development and its Application for Predicting Optical Properties in Molecular Space: ChemML Program Suite, Machine Learning in Science and Engineering<\/i>&#8220;, Atif will have a poster on Friday on &#8220;<i>Harnessing Virtual High-Throughput Screening and Machine Learning for the Discovery of Novel High-Refractive-Index Polymers<\/i>&#8220;, and Johannes will give an invited talk discussing &#8220;<i>Advancing Molecular Property Predictions and Design with Machine Learning<\/i>&#8221; on Friday as well. All presentations are part of the MLSE Symposium on Predicting Molecular Properties and Molecular Design.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Atif, Mojtaba, and Johannes are in Pittsburgh (PA) this week for Machine Learning in Science and Engineering 2018. Mojtaba will present a poster on Wednesday titled &#8220;Software Development and its Application for Predicting Optical Properties in Molecular Space: ChemML Program Suite, Machine Learning in Science and Engineering&#8220;, Atif will have a poster on Friday on &#8220;Harnessing Virtual High-Throughput Screening and Machine Learning for the Discovery of Novel High-Refractive-Index Polymers&#8220;, and Johannes will give an invited talk discussing &#8220;Advancing Molecular Property Predictions and Design with Machine Learning&#8221; on Friday as well. All presentations are part of the MLSE Symposium on Predicting Molecular Properties and Molecular Design.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[25,7],"tags":[],"class_list":["post-2479","post","type-post","status-publish","format-standard","hentry","category-conferences","category-news","entry","post-inner"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.9 - aioseo.com -->\n\t<meta name=\"description\" content=\"Atif, Mojtaba, and Johannes are in Pittsburgh (PA) this week for Machine Learning in Science and Engineering 2018. Mojtaba will present a poster on Wednesday titled &quot;Software Development and its Application for Predicting Optical Properties in Molecular Space: ChemML Program Suite, Machine Learning in Science and Engineering&quot;, Atif will have a poster on Friday on\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"jhachmann\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/atif-mojtaba-and-johannes-at-mlse-2018\/\" \/>\n\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 4.9.9\" \/>\n\t\t<meta property=\"og:locale\" content=\"en_US\" \/>\n\t\t<meta property=\"og:site_name\" content=\"Hachmann Research Group @ UB | Welcome to the Hachmann Research Group!\" \/>\n\t\t<meta property=\"og:type\" content=\"activity\" \/>\n\t\t<meta property=\"og:title\" content=\"Atif, Mojtaba, and Johannes at MLSE 2018 | Hachmann Research Group @ UB\" \/>\n\t\t<meta property=\"og:description\" content=\"Atif, Mojtaba, and Johannes are in Pittsburgh (PA) this week for Machine Learning in Science and Engineering 2018. 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