Active Learning for Molecular Design

This lecture by the instructor covers the basics of machine learning approaches to replacing the process of creating ideas for materials to test, inferring if they are feasible, and designing experiments. The talk delves into the theory behind such techniques, provides practical examples from recent literature, and identifies example software as starting points for using these techniques in research. The lecture progresses from discussing the role of the instructor in various projects to highlighting the importance of education in AI for materials. It also touches on the challenges and advancements in generative AI for assisting human creativity in material design.