Enabling Chemical Synthesis via Machine Learning
Abigail G. Doyle
University of California, Los Angeles
The Doyle lab conducts research at the interface of organic, organometallic, physical organic, and computational chemistry. Our goal is to address unsolved problems in organic synthesis through the development of catalysts, catalytic reactions, and synthetic methods. We apply mechanistic and computer-assisted techniques to the analysis of these reactions in order to uncover general principles that can guide the design of improved ligands, catalysts and the discovery of new reactions. These studies have also included the development of machine learning tools for reaction optimization, prediction and mechanistic inference. This lecture will describe our integrated efforts to develop, assess, and deploy machine learning tools in reaction and catalyst design.

speaker

Cheng-Chung Wang
Statistical and AI Analysis on Stereoselective Glycosylation Reactions and their Mechanisms

Yen-Ku Wu
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Chun-Guey Wu
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