{"id":17942,"date":"2025-10-15T18:58:02","date_gmt":"2025-10-15T16:58:02","guid":{"rendered":"https:\/\/ist.kpi.ua\/?p=17942"},"modified":"2025-10-15T19:01:14","modified_gmt":"2025-10-15T17:01:14","slug":"lecture-training-neural-networks-for-robotic-manipulation","status":"publish","type":"post","link":"https:\/\/ist.kpi.ua\/en\/blog\/lecture-training-neural-networks-for-robotic-manipulation\/","title":{"rendered":"Lecture: Training Neural Networks for Robotic Manipulation"},"content":{"rendered":"<p>We invite you to a guest lecture by Peter Prettenhofer: &#8220;Vision-based policy learning for robotics and dexterous manipulation&#8221;.<\/p>\n<p>Peter will talk about the latest approaches to Embodied AI &#8211; embodied artificial intelligence that combines perception, movement and learning for robots. From ALOHA, ACT, Diffusion Policy systems, to universal RT-X, OpenVLA, Pi Zero models. In the second half of the lecture there will be a question and answer session!<\/p>\n<p>Speaker:<br \/>\n\u2022\u00a0 Principal Research Engineer, Neo Cybernetica, working on Embodied AI systems for robotic manipulation;<br \/>\n\u2022\u00a0 Former VP of Engineering at DataRobot, a pioneer in the field of automated machine learning (AutoML);<br \/>\n\u2022 Co-author of the scikit-learn library (Gradient Boosted Trees, SGD, Decision Trees);<br \/>\n\u2022 Specializes in machine learning and computer vision in robotics.<\/p>\n<p><a href=\"https:\/\/docs.google.com\/forms\/d\/e\/1FAIpQLSf745TGBDhwt4L1hbYDzfEHTSuQq60H3lUePVpnJaIT6f694w\/viewform\">Registration<\/a><br \/>\nOctober 17, 17:00<br \/>\nZoom<\/p>\n<p>Feedback \u2014 @titardrew<\/p>\n<p><a href=\"https:\/\/t.me\/dnvr_31\">Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We invite you to a guest lecture by Peter Prettenhofer: &#8220;Vision-based policy learning for robotics and dexterous manipulation&#8221;. Peter will talk about the latest approaches to Embodied AI &#8211; embodied artificial intelligence that combines perception, movement and learning for robots. From ALOHA, ACT, Diffusion Policy systems, to universal RT-X, OpenVLA, Pi Zero models. In the [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":17940,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[18],"tags":[],"class_list":["post-17942","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/posts\/17942","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/comments?post=17942"}],"version-history":[{"count":1,"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/posts\/17942\/revisions"}],"predecessor-version":[{"id":17943,"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/posts\/17942\/revisions\/17943"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/media\/17940"}],"wp:attachment":[{"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/media?parent=17942"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/categories?post=17942"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ist.kpi.ua\/en\/wp-json\/wp\/v2\/tags?post=17942"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}