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Connor W. Coley is an Assistant Professor at MIT in the Department of Chemical Engineering and the Department of Electrical Engineering and Computer Science. He received his B.S. and Ph.D. in Chemical Engineering from Caltech and MIT, respectively, and did his postdoctoral training at the Broad Institute. His research group at MIT develops new methods at the intersection of data science, chemistry, and laboratory automation to streamline discovery in the chemical sciences with an emphasis on therapeutic discovery. Key research areas in the group include the design of new neural models for representation learning on molecules, data-driven synthesis planning, in silico strategies for predicting the outcomes of organic reactions, model-guided Bayesian optimization, and de novo molecular generation. Connor is a recipient of C&EN’s “Talented Twelve” award, Forbes Magazine’s “30 Under 30” for Healthcare, the NSF CAREER award, and the Bayer Early Excellence in Science Award.