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PRODID:-//Kentico Software//NONSGML Kentico CMS//EN
VERSION:2.0
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UID:c962c8b8-083e-4c72-806f-5a42b9399f2f@avs.org
DTSTAMP:20260429T184118Z
DTSTART:20240328T170000Z
DTEND:20240328T210000Z
LOCATION: Virtual/Online
DESCRIPTION:\nAs Python-based APIs from major equipment manufacturers are becoming increasingly available, automated experimentation is now accessible to a broad range of scientists in both academia and industry. This webinar is tailored to meet these evolving needs. It is specifically designed to bridge the gap between theoretical data science concepts and their applications in automated microscopy, focusing on developing practical experimental workflows. The course provides an in-depth physicist's perspective on Bayesian methods and includes introduction into the GPax library. This approach is aimed at developing both intuition and practical skills necessary for applying Bayesian optimization in real-world experimental settings. Building upon optimization, we will discuss the construction of multistep workflows targeted at discovery of structure-property relationships, identifying physical laws, co-navigation between theory and experimental spaces, and co-orchestration of several tools. By the end of the course, attendees are expected to have a comprehensive understanding of how to apply Bayesian optimization methods effectively for simple tasks such as image optimization, and extend them to real world physics and materials science problems, making this course an invaluable resource for those looking to harness the full potential of ML/AI for modern experimental science.\n\n Virtual/Online\n\n Heather Korff
SUMMARY: AVS Webinar: Automated Experiment in Scanning Probe and Electron Microscopy
PRIORITY:3
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