{"id":247,"date":"2025-04-28T10:41:52","date_gmt":"2025-04-28T13:41:52","guid":{"rendered":"https:\/\/pages.cnpem.br\/MLSchool\/?page_id=247"},"modified":"2025-04-28T10:44:23","modified_gmt":"2025-04-28T13:44:23","slug":"ml-school-2023","status":"publish","type":"page","link":"https:\/\/pages.cnpem.br\/EncontroIA\/ml-school-2023\/","title":{"rendered":"Machine Learning School for Materials (2023)"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row][vc_column]<style type=\"text\/css\" data-type=\"the7_shortcodes-inline-css\">.shortcode-single-image-wrap.shortcode-single-image-cb0ec46a06471873913e93fa8b253a00.enable-bg-rollover .rollover i,\n.shortcode-single-image-wrap.shortcode-single-image-cb0ec46a06471873913e93fa8b253a00.enable-bg-rollover .rollover-video i {\n  background: -webkit-linear-gradient();\n  background: linear-gradient();\n}\n.shortcode-single-image-wrap.shortcode-single-image-cb0ec46a06471873913e93fa8b253a00 .rollover-icon {\n  font-size: 32px;\n  color: #ffffff;\n  min-width: 44px;\n  min-height: 44px;\n  line-height: 44px;\n  border-radius: 100px;\n  border-style: solid;\n  border-width: 0px;\n}\n.dt-icon-bg-on.shortcode-single-image-wrap.shortcode-single-image-cb0ec46a06471873913e93fa8b253a00 .rollover-icon {\n  background: rgba(255,255,255,0.3);\n  box-shadow: none;\n}<\/style><div class=\"shortcode-single-image-wrap shortcode-single-image-cb0ec46a06471873913e93fa8b253a00 alignnone  enable-bg-rollover dt-icon-bg-off\" style=\"margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px;\"><div class=\"shortcode-single-image\"><div class=\"fancy-media-wrap  layzr-bg\" style=\"\"><img fetchpriority=\"high\" decoding=\"async\" class=\"preload-me lazy-load aspect\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D&#39;http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg&#39;%20viewBox%3D&#39;0%200%20758%20532&#39;%2F%3E\" data-src=\"https:\/\/pages.cnpem.br\/EncontroIA\/wp-content\/uploads\/sites\/143\/2025\/04\/ml-school-2023.jpg\" data-srcset=\"https:\/\/pages.cnpem.br\/EncontroIA\/wp-content\/uploads\/sites\/143\/2025\/04\/ml-school-2023.jpg 758w\" loading=\"eager\" sizes=\"(max-width: 758px) 100vw, 758px\" width=\"758\" height=\"532\"  data-dt-location=\"https:\/\/pages.cnpem.br\/EncontroIA\/ml-school-2023\/ml-school-2023-2\/\" style=\"--ratio: 758 \/ 532;\" alt=\"\" \/><\/div><\/div><\/div>[vc_empty_space height=&#8221;32 px&#8221;][vc_column_text css=&#8221;&#8221;]<\/p>\n<h2 style=\"text-align: justify;\">2\u00b0 Encontro de Intelig\u00eancia Artificial: Machine Learning School for Materials (2023)<\/h2>\n<p style=\"text-align: justify;\">The event aims to bridge the gap between the scientific community working in Machine Learning and Materials Science and the future generation of scientists interested in this field. The main objective is to consolidate the field of Machine Learning for Materials in Brazil.<\/p>\n<h3 style=\"text-align: justify;\">Event format<\/h3>\n<p style=\"text-align: justify;\">The event will be hybrid (in-person + online) and will last two days. It will include hands-on tutorials at the undergraduate level and a poster session. There is a registration fee of 50,00 reais for in-person attendance, while there is no registration fee for the online modality.<\/p>\n<h3>Scientific committee<\/h3>\n<p>Adalberto Fazzio (Ilum\/CNPEM)<br \/>\nAmauri J. de Paula (Ilum\/CNPEM)<br \/>\nDaniel Roberto Cassar (Ilum\/CNPEM)\u00a0<strong>CHAIR<\/strong><br \/>\nJames Mores de Almeida (Ilum\/CNPEM)\u00a0<strong>CHAIR<\/strong><br \/>\nFelipe D. C. de Lima (Ilum\/CNPEM)<br \/>\nGustavo Dalpian (UFABC)[\/vc_column_text][vc_empty_space][\/vc_column][\/vc_row][vc_row][vc_column][vc_text_separator title=&#8221;Agenda&#8221;][vc_accordion active_tab=&#8221;1&#8243; style=&#8221;2&#8243;][vc_accordion_tab title=&#8221;September 18&#8243;][vc_column_text]<\/p>\n<table style=\"border-collapse: collapse; width: 80.9699%; height: 259px;\">\n<tbody>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; text-align: center; height: 22px;\"><strong>Speaker\/Activity<\/strong><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><strong>Starts at<\/strong><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><strong>Ends at<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><span class=\"ui-provider ha b c d e f g h i j k l m n o p q r s t u v w x y z ab ac ae af ag ah ai aj ak\" dir=\"ltr\">Oppening<\/span><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">8:45<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">9:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Maicon Louren\u00e7o<\/strong>:<em> Artificial Intelligence for Chemistry and Materials Science \u2013 from Automatic Structural Determination to Prediction of New Materials<\/em><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">9:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">10:30<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Coffee break<\/strong><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">10:30<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">11:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><span class=\"ui-provider ha b c d e f g h i j k l m n o p q r s t u v w x y z ab ac ae af ag ah ai aj ak\" dir=\"ltr\"><strong>Maicon Louren\u00e7o:<\/strong>\u00a0<em>Artificial Intelligence for Chemistry and Materials Science \u2013 from Automatic Structural Determination to Prediction of New Materials<\/em><\/span><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">11:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">12:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Lunch<\/strong><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">12:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">14:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Daniel Cassar<\/strong>:\u00a0<em>Finding new materials with AI (and learning something new in the process)<\/em><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">14:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">15:30<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Coffee break<\/strong><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">15:30<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">16:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Daniel Cassar<\/strong>:\u00a0<em>Finding new materials with AI (and learning something new in the process)<\/em><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">16:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">17:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 17px; text-align: center;\"><em><span class=\"ui-provider ha b c d e f g h i j k l m n o p q r s t u v w x y z ab ac ae af ag ah ai aj ak\" dir=\"ltr\">Poster session<\/span><\/em><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 17px;\">17:00<\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 17px;\">18:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; text-align: center; height: 22px;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; text-align: center; height: 22px;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>[\/vc_column_text][\/vc_accordion_tab][vc_accordion_tab title=&#8221;September 19&#8243;][vc_column_text]<\/p>\n<table style=\"border-collapse: collapse; width: 80.9699%; height: 242px;\">\n<tbody>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; text-align: center; height: 22px;\"><strong>Speaker\/Activity<\/strong><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><strong>Starts at<\/strong><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><strong>Ends at<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Marcos Quiles<\/strong>:<em> Introduction to deep learning and its application in chemistry and materials.<\/em><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">9:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">10:30<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Coffee break<\/strong><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">10:30<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">11:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Marcos Quiles<\/strong>:<em> Introduction to deep learning and its application in chemistry and materials.<\/em><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">11:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">12:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Lunch<\/strong><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">12:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">14:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Gabriel Schleder<\/strong>:\u00a0<em>Data science without data? Solving partial differential equations of quantum systems using Physics-informed Neural Networks (PINNs)<\/em><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">14:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">15:30<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Coffee break<\/strong><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">15:30<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">16:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><strong>Gabriel Schleder<\/strong>:\u00a0<em>Data science without data? Solving partial differential equations of quantum systems using Physics-informed Neural Networks (PINNs)<\/em><\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">16:00<\/td>\n<td style=\"width: 14.5827%; height: 22px; text-align: center;\">17:00<\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<\/tr>\n<tr style=\"height: 22px;\">\n<td style=\"width: 25%; height: 22px; text-align: center;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<td style=\"width: 14.5827%; text-align: center; height: 22px;\"><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>[\/vc_column_text][\/vc_accordion_tab][\/vc_accordion][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_empty_space height=&#8221;32 px&#8221;][vc_column_text css=&#8221;&#8221;] 2\u00b0 Encontro de Intelig\u00eancia Artificial: Machine Learning School for Materials (2023) The event aims to bridge the gap between the scientific community working in Machine Learning and Materials Science and the future generation of scientists interested in this field. The main objective is to consolidate the field of Machine Learning for&hellip;<\/p>\n","protected":false},"author":883,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-247","page","type-page","status-publish","hentry","description-off"],"_links":{"self":[{"href":"https:\/\/pages.cnpem.br\/EncontroIA\/wp-json\/wp\/v2\/pages\/247","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pages.cnpem.br\/EncontroIA\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pages.cnpem.br\/EncontroIA\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pages.cnpem.br\/EncontroIA\/wp-json\/wp\/v2\/users\/883"}],"replies":[{"embeddable":true,"href":"https:\/\/pages.cnpem.br\/EncontroIA\/wp-json\/wp\/v2\/comments?post=247"}],"version-history":[{"count":0,"href":"https:\/\/pages.cnpem.br\/EncontroIA\/wp-json\/wp\/v2\/pages\/247\/revisions"}],"wp:attachment":[{"href":"https:\/\/pages.cnpem.br\/EncontroIA\/wp-json\/wp\/v2\/media?parent=247"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}