Connor W. Coley
Assistant Professor of Chemical Engineering
Assistant Professor of Electrical Engineering and Computer Science

Bio: 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. Outside of MIT, Connor serves as an advisor to both early- and late-stage companies including Entos, Revela, Galixir, Kebotix, Anagenex, ArrePath, and Dow.

Postdoctoral Associates & Fellows and Research Scientists

Fanwang Meng
Postdoctoral Associate

Fanwang completed his PhD in chemistry in 2021 with Prof. Paul W. Ayers at McMaster University. He then worked as a postdoc fellow in Ayers Lab before joining Coley group in September, 2022. He is interested in synthesis planning and lab automation with a special focus on drug design.

Guangqi Wu
Postdoctoral Associate

Guangqi completed his PhD in Polymer Chemistry and Physics with Prof. Hua Lu from Peking University in 2020. Then he stayed in the group as Boya Postdoctoral Fellow before joining Coley group in June 2022. He is interested in applying machine learning and polymer informatics to guide polymer synthesis and screening.

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.

Joonyoung Joung
Postdoctoral Associate

Joonyoung received his Ph.D. degree in Physical Chemistry from Korea University in 2020. Then he stayed in the group as a Research Professor and Postdoctoral Associate before joining Coley group in September 2022. He is interested in developing machine learning methods to find the best process in process chemistry.

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.

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.

Graduate Students

Christian Ulmer
Visiting MS Student

Christian received his BS in Chemical Engineering from TU Berlin and is a master's student in Computer Simulations for Science and Engineering at TU Berlin and KTH Stockholm. His master's thesis project focuses on synthesizability-constrained molecular generation using deep learning.

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.

Edward Jin
MEng Student

Edward is an MEng student, having studying chemistry and EECS at MIT as an undergraduate. Previously, he worked in organic synthesis and in chemoinformatics. He is interested in developing computational models of reactivity that are based on fundamental chemical properties.

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.

Itai Levin
PhD Student

Itai received his B.A. in Chemistry and Chemical Biology from Cornell and is a PhD student at MIT in Biological Engineering, co-advised with Chris Voigt. He is interested in improving computer-aided synthesis planning for pathways that involve enzymatic catalysis.

Jenna Fromer
PhD Student

Jenna received her BS in Chemical Engineering from Tufts University in May 2021 and is now a PhD student at MIT in Chemical Engineering. She is interested in utilizing multi-objective optimization with synthetic cost considerations to accelerate molecular discovery.

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.

Mingrou Xie
PhD Student

Mingrou received her M.Eng in Chemical Engineering from Imperial College London in 2020 and worked for a year in Singapore before joining MIT. As a co-supervised PhD student with Professor Rafael Gómez-Bombarelli from DMSE, she is interested in engineering green chemistry through catalysis. Her current research focuses on chemical reactivity in porous materials using computational chemistry and ML.

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.

Samuel Goldman
PhD Student

Sam received his A.B. in Computer Science from Harvard in 2019 and is a PhD student at MIT in Computational and Systems Biology. He is interested in using machine learning methods to develop better models of enzymatic catalysis.

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.

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.

Undergraduate and Postgraduate Researchers

Lab Alumni

  • Rebecca Neeser (MS 2022, ETH Zurich) → PhD Student
  • Matteo Aldeghi (Research Scientist) → Senior Research Scientist @ Google Research
  • Aparajita Dasgupta (Postdoctoral Associate) → Senior Scientist, Process Development @ Pfizer
  • Katherine Lim (UG 2023, MIT)
  • Jacob Yasonik (UG 2024, MIT) → Intern @ Google Brain
  • Min Htoo Lin (UG 2021, Nanyang Technological University) → Deep Learning Algorithm Engineer @ ADVANCE.AI → AI Engineer @ Talo Labs
  • Tyra Jones (UG 2021, Spelman College & UG 2023, Georgia Tech)
  • Jackson Burns (UG 2022, University of Delaware) → PhD Student @ MIT