{"id":639,"date":"2018-05-13T10:12:25","date_gmt":"2018-05-13T14:12:25","guid":{"rendered":"https:\/\/events.mcs.cmu.edu\/mlse\/?page_id=639"},"modified":"2018-05-29T12:04:29","modified_gmt":"2018-05-29T16:04:29","slug":"chemical-engineering-program","status":"publish","type":"page","link":"https:\/\/events.mcs.cmu.edu\/mlse\/chemical-engineering-program\/","title":{"rendered":"Chemical Engineering Program"},"content":{"rendered":"<div id=\"pl-639\" class=\"panel-layout\">\n<div id=\"pg-639-0\" class=\"panel-grid panel-no-style\">\n<div id=\"pgc-639-0-0\" class=\"panel-grid-cell\">\n<div id=\"panel-639-0-0-0\" class=\"so-panel widget widget_sow-editor panel-first-child\">\n<div class=\"so-widget-sow-editor so-widget-sow-editor-base\">\n<div class=\"siteorigin-widget-tinymce textwidget\">\n<h2>JUNE 7th<\/h2>\n<ul>\n<li><strong>Session Topic- Surface Science &amp; Catalysis<\/strong><\/li>\n<li>8:30-9:00- Andrew Medford (Georgia Institute of Technology) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/MLSE_abstract-2.pdf\">Catalysis Informatics: Utilizing machine-learning and data science to extract knowledge from catalytic data<\/a>\u201d<\/li>\n<li>9:00-9:30- Zack Ulissi (Carnegie Mellon) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/mlse_abstract.txt\">Practical Applications of Machine Learning to Catalyst Design and Discovery<\/a>\u201d<\/li>\n<li>9:30-10:00- Richard West (Northeastern University) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/MLSE-abstract-rxn2vec.docx\">Unsupervised Machine Learning for Data-Driven Representation of Reactions<\/a>\u201d<\/li>\n<li>10:00-10:30- Hongliang Xin (Virginia Polytechnic Institute) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/ML-Xin.docx\">Machine Learning for Understanding Nonadiabatic Surface Chemistry and Accelerating Catalyst Discovery<\/a>\u201d<\/li>\n<li>break<\/li>\n<li>Dion Vlachos (University of Delaware) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/Vlachos_Abstract-PredictiveModelingMachineLearning_CMUMtg.doc\">Predictive Modeling of Complex Chemical Reactions: Correlated Data, Uncertainty Quantification, and Machine Learning<\/a>\u201d<\/li>\n<li>11:00-11:30- Andreas Heyden (University of South Carolina) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/Identifying-the-active-site-of-the-water.docx\">Identifying the active site of the water-gas shift reaction over platinum-based catalysts<\/a>\u201d<\/li>\n<li>11:30-12:00- Bryan Goldsmith (University of Michigan) \u2013 \u201cFinding descriptors in materials data using subgroup discovery and compressed sensing\u201d<\/li>\n<li>12:00-12:30- Srinivas Rangarajan (Lehigh University) \u2013 \u201cHarnessing systems and informatics approaches in mechanistic analysis of catalytic chemistries\u201d<\/li>\n<li>12:30-1:30- lunch\/posters<\/li>\n<li>1:30-2:30- plenary<\/li>\n<li><strong>Session Topic &#8211; Systems Engineering<\/strong><\/li>\n<li>2:30-3:00- Fani Boukouvala (Georgia Institute of Technology) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/ML_Abstract_Boukouvala.pdf\">Best surrogate approximations for data-driven optimization<\/a>\u201d<\/li>\n<li>3:00-3:30- Bhusan Golupani (University of British Columbia) \u2013 \u201cDeep Neural Networks for Supervised and Unsupervised Learning of Process Faults\u201d<\/li>\n<li>3:30-4:00- Lorenz Biegler (Carnegie Mellon University) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/2018\/04\/Biegler-MLSE-abstract-template-1.docx\">Data-driven optimization with Truth Models<\/a>\u201d<\/li>\n<li>break-<\/li>\n<li>Venkat Venkatasubramanian (Columbia University) \u2013 \u201cMachine Learning in Process Systems Engineering: Opportunities and Challenges\u201d<\/li>\n<li>4:30-5:00- Luke Achenie (Virginia Polytechnic Institute) \u2013 \u201cODEs as Machine Learners?\u201d<\/li>\n<li>5:00-5:30- Victor Zavala (University of Wisconsin-Madison) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/abstractml2018.pdf\">Machine Learning Algorithms for Liquid Crystals-Based Sensors<\/a>\u201d<\/li>\n<li>5:30-6:00- Heather Mayes (University of Michigan) \u2013 \u201cProviding the Foundation for Chemical Engineers to Become Data Scientists\u201d<\/li>\n<\/ul>\n<p>JUNE 8th<\/p>\n<ul>\n<li>9:00-9:30<\/li>\n<li>9:30-10:00-<\/li>\n<li>10:00-10:30<\/li>\n<li><strong>break<\/strong><\/li>\n<li>11:00-11:30<\/li>\n<li>11:30-12:00<\/li>\n<li>12:00-12:30<\/li>\n<li>12:30-1:30- lunch\/posters<\/li>\n<li>1:30-2:30- plenary<\/li>\n<li><strong>session topic<\/strong><\/li>\n<li>2:30-3:00<\/li>\n<li>3:00-3:30<\/li>\n<li>3:30-4:00<\/li>\n<li><strong>break<\/strong><\/li>\n<li>4:30-5:00<\/li>\n<li>5:00-5:30<\/li>\n<li>5:30-6:00<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<div id=\"panel-639-0-0-1\" class=\"so-panel widget widget_sow-editor panel-last-child\">\n<div class=\"so-widget-sow-editor so-widget-sow-editor-base\">\n<div class=\"siteorigin-widget-tinymce textwidget\">\n<h3 style=\"text-align: center\">Posters<\/h3>\n<p>Hemanth Pillai (Virginia Polytechnic Institute) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/Abstract_Metalloporphyrin_MOFs.docx\">A Machine Learning Model for Accelerating Biomimetic Electrocatalyst Discovery<\/a>\u201d<\/p>\n<p>Jiamin Wang (Virginia Polytechnic Institute) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/abstract.pdf\">Machine Learning Molecular Dynamics for Understanding Nonadiabatic Surface Reactions<\/a>\u201d<\/p>\n<p>Jinchao Feng (University of Massachusetts Amherst) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/abstract_mlse.docx\">Model-Form Uncertainty Quantification in Fuel Cell Design<\/a>\u201d<\/p>\n<p>Aini Palizhati (Carnegie Mellon University) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/MLSE-2018_Palizhati.pdf\">Using Data Science to Reduce Large Reaction Networks in Catalysis<\/a>\u201d<\/p>\n<p>Jiazhou Zhu (Clemson University) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/Abstract_JZZ.pdf\">Expanding Methods from Computationally-Driven Design of Catalysts to Designing Advanced Materials<\/a>\u201d<\/p>\n<p>Junwoong Yoon (Carnegie Mellon University) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/MLSE_abstract-1.pdf\">Surfactant Design with Molecular Simulations and Machine Learning<\/a>\u201d<\/p>\n<p>Dilip Krishnamurthy (Carnegie Mellon University) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/2018\/05\/ChemE-Krishnamurthy.pdf\">Machine Learning Generalized Geometric Descriptors for Oxygen Reduction Activity on Transition Metal Sulfides<\/a>\u201d<\/p>\n<p>Kevin Tran (Carnegie Mellon University) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/MLSE2018-abstract.docx\">Active learning across intermetallics to guide discovery of electrocatalysts for CO2 reduction and H2 evolution<\/a>\u201d<\/p>\n<p>Ray Lei (Georgia Institute of Technology) \u2013 \u201c<a href=\"https:\/\/events.mcs.cmu.edu\/mlse\/wp-content\/uploads\/sites\/2\/ninja-forms\/2\/CMU-symposium-Abstract-final.docx\">Data-driven Exchange-Correlation Functional Design and Visualization of Electronic Environments<\/a>\u201d<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>JUNE 7th Session Topic- Surface Science &amp; Catalysis 8:30-9:00- Andrew Medford (Georgia Institute of Technology) \u2013 \u201cCatalysis Informatics: Utilizing machine-learning and data science to extract knowledge from catalytic data\u201d 9:00-9:30- Zack Ulissi (Carnegie Mellon) \u2013 \u201cPractical Applications of Machine Learning to Catalyst Design and Discovery\u201d 9:30-10:00- Richard West (Northeastern University) [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":5,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/template-fullwidth.php","meta":{"footnotes":""},"class_list":["post-639","page","type-page","status-publish","has-post-thumbnail","hentry"],"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/P9mDlk-aj","_links":{"self":[{"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/pages\/639","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/comments?post=639"}],"version-history":[{"count":13,"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/pages\/639\/revisions"}],"predecessor-version":[{"id":910,"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/pages\/639\/revisions\/910"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/media\/5"}],"wp:attachment":[{"href":"https:\/\/events.mcs.cmu.edu\/mlse\/wp-json\/wp\/v2\/media?parent=639"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}