Organic Chemistry Seminar: Abby Doyle, University of California, Los Angeles
About the Seminar
Enabling Chemical Synthesis via Machine Learning
Machine learning (ML), the development and study of computer algorithms that learn from data, is increasingly important across a wide array of applications, from virtual personal assistants to social media and product recommendation systems. ML methods have also driven key developments in the natural sciences: virtual screening of drug-like molecules for medical applications, rapid prediction of physical data, and computer-aided synthesis planning have all been facilitated by ML. The development of ML tools for synthetic methodology development and catalysis could enable chemists to make data-efficient choices and learn from that data in the course of reaction prediction, reaction condition optimization, and mechanistic interrogation. This lecture will describe my group’s efforts to develop and apply open-source data science tools to numerous aspects of synthetic methodology development, including substrate scope design, ligand design, reaction optimization and mechanistic elucidation.
About the Speaker
Abby Doyle is the Saul Winstein Chair in Organic Chemistry at the University of California, Los Angeles. She received her A.B. and A.M. summa cum laude in Chemistry and Chemical Biology from Harvard University in 2002. She began her graduate studies at Stanford University working with Professor Justin Du Bois before moving to Harvard University in 2003, where she obtained her PhD in the laboratory of Professor Eric Jacobsen. Abby began her independent career at Princeton University in 2008, was promoted to Associate Professor in 2013 and A. Barton Hepburn Professor in 2015. In 2021, she and her research group moved to UCLA where they conduct research at the interface of organic, organometallic, and physical organic chemistry, enhanced by the use of modern data science and machine learning tools. The Doyle lab has addressed unsolved problems in organic synthesis through the development of novel catalysts, catalytic reactions, and synthetic methods. They have also implemented mechanistic and computer-assisted techniques to uncover general chemical principles, predict unseen reactivity, and discover new reactions. Abby is a senior editor for Accounts of Chemical Research. She has been recognized recently by the OMCOS award (2023), Blavatnik National Award for Young Scientists (Finalist, 2022), EJ Corey Award for Outstanding Original Contribution in Organic Synthesis by a Young Investigator (2022) and The Camille and Henry Dreyfus Foundation Machine Learning in the Chemical Sciences and Engineering Award (2021).