Connor W. Coley
Assistant Professor of Chemical Engineering
Assistant Professor of Electrical Engineering and Computer Science
Connor received his B.S. in Chemical Engineering from Caltech and his Ph.D. in Chemical Engineering MIT. His research interests are in how data science and laboratory automation can be used to streamline discovery in the chemical sciences.
Postdoctoral Associates & Fellows and Research Scientists
Thijs Stuyver
Postdoctoral Associate
Thijs received his PhD in Chemistry from the Free University of Brussels in June 2018. Subsequently, he moved to Israel to work with Prof. Sason Shaik at the Hebrew University of Jerusalem before joining the Coley research group in April 2021. He is interested in augmenting machine learning models for reaction prediction and discovery with the help of expert knowledge in physical organic chemistry.
Matteo Aldeghi
Research Scientist
Matteo completed his PhD in Biochemistry from Oxford in 2016. He later moved to Germany to work in Bert de Groot's group at the Max Planck Institute for Biophysical Chemistry as a Humboldt Research Fellow. In July 2019, he joined Alán Aspuru-Guzik's group as a Vector Postdoctoral Fellow, before joining the Coley research group in June 2021. Matteo is broadly interested in the use of data-driven as well as physics-based computational approaches in chemical and pharmaceutical research.
Rocío Mercado
Postdoctoral Associate
Rocío received her PhD in Chemistry from UC Berkeley in 2018, after which she did an industrial postdoc in the Molecular AI team at AstraZeneca before joining the Coley group August 2021. Her research interests lie at the intersection of chemistry and artificial intelligence for molecular discovery, with a recent focus on deep generative models for small molecule drug design.
John Bradshaw
Postdoctoral Associate
John completed his PhD in Engineering at the University of Cambridge and the Max Planck Institute for Intelligent Systems, graduating in the summer of 2021. He joined the Coley Research Group shortly afterwards and is interested in developing machine learning methods to augment researchers in the design-make-test steps of new molecule design.
Graduate Students
David Graff
PhD Student
David completed his B.A. in Chemistry at Princeton and is now working on his Ph.D. in Chemistry at Harvard as a joint student between the Coley group and the Shakhnovich group. His work focuses on using optimization and machine learning to accelerate the discovery of drug-like molecules.
Priyanka Raghavan
PhD Student
Priyanka graduated from UC Berkeley with a B.S. in Chemical Engineering, where she used quantum science to engineer new generation MRI machines and biological imaging techniques. Working towards her PhD at MIT, she is exploring problems involving intelligent discovery using AI/ML, directed evolution, combinatorial chemistry, and robotics.
Zhengkai Tu
SM Student
Zhengkai received his B.ASc. in Chemical Engineering from Waterloo and is a master student at MIT in Computational Science and Engineering. He previously worked on deep learning applications in NLP and is currently interested in using machine learning for reaction prediction and retrosynthesis.
Wenhao Gao
PhD Student
Wenhao received his B.S. in Chemistry from Peking University and his M.S. in Chemical and Biomolecular Engineering from Johns Hopkins University. He joined the group in 2020 and his research interest focuses on using artificial intelligence and robotic automation to accelerate biological and chemical discovery processes.
Keir Adams
PhD Student
Keir received his B.S. in Chemistry and Molecular Engineering from the University of Chicago in 2020 and is now a PhD student in Chemical Engineering and Computation at MIT. His research focuses on advancing molecular representation for machine learning-assisted chemical discovery.
Herry (Tianyi) Jin
PhD Student
Herry received his B.S. in Chemical Engineering and Mathematics from UW-Madison in 2020 and now is a PhD student at MIT in Chemical Engineering, co-advised with Alfredo Alexander-Katz. He is interested in using machine learning and molecular modeling to promote enzyme stability via random copolymers.
Ria Das
MEng Student
Ria is an M.Eng. in Computer Science studying program synthesis and artificial intelligence, with a particular focus on how ideas from program synthesis may be used to build more human-like AI. She recently became curious about the application of program synthesis/AI to the life sciences and other applied fields, and is interested in learning more about these domains part-time in the group.
