Connor W. Coley is an Assistant Professor at MIT in the Departments of Chemical Engineering & 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 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.
Through this fellowship, Connor will develop AI models for scientific discovery that help us both plan and execute experiments. By augmenting intuition with information-driven decision making, he hopes to design autonomous laboratories that accelerate the creation of new medicines and other useful products.
R. Mercado, S. Kearnes, and C.W. Coley. Data sharing in chemistry: lessons learned and a case for mandating structured reaction data. J. Chem. Inf. Model. 2023.
N. David, W. Sun, and C.W. Coley. The promise and pitfalls of AI for molecular and materials synthesis. Nature Computational Science. 2023.