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, the Bayer Early Excellence in Science Award, and is a Schmidt Futures AI2050 Early Career Fellow.
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.
Qianxiang Ai
Research Scientist
Qianxiang completed his PhD in chemistry in 2020 with Chad Risko at the University of Kentucky. He then worked with Joshua Schrier as a postdoc at Fordham University before joining the Coley group in Jan, 2023. He is interested in data infrastructures related to experiment planning and automation.
Graduate Students
Anji Zhang
PhD Student
Anji graduated from the University of Toronto with a B.S. in Chemistry, where she worked on reaction methodology and automation. She is now pursuing her PhD in Chemistry at MIT as a co-advised student with Timothy Jamison, where her research focuses on using machine learning for reaction outcome prediction and data-driven reaction optimization.
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.
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.
Joules Provenzano
PhD Student
Joules received their B.S. in Chemical Engineering and Global Studies at Rochester Institute of Technology and is now a PhD student at MIT in Chemical Engineering. Co-advised by Desirée Plata, Joules uses experimental and data-driven methods to better understand environmental degradation pathways of complex mixtures.
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.
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.
Xiaoqi Sun
PhD Student
Xiaoqi graduated from UC Berkeley with a B.A. in Data Science and a B.S. in Chemical Engineering in 2022. As a PhD student in Chemical Engineering at MIT, she is interested in exploring autonomous data-driven synthesis and applying machine learning to reaction prediction problems.
Zhengkai Tu
PhD Student
Zhengkai received his B.ASc. in Chemical Engineering from Waterloo and S.M. from 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
- Jiayi Xin, HKU Applied Artificial Intelligence / Wellesley College
- Saul A. Vega Sauceda, MIT Computer Science and Molecular Biology (LinkedIn)
- Janet Li, Harvard Computer Science and Statistics (Chemistry minor)
- Divya Nori, MIT Chemical Engineering and EECS
- Chanwoo Yoon, MIT Electrical Engineering and Computer Science
- Ron Shprints, MIT Mathematics with Computer Science
Lab Alumni
- Rocío Mercado (Postdoctoral Associate) → Assistant Professor @ Chalmers (group page)
- Thijs Stuyver (Postdoctoral Associate) → Assistant Professor @ Université PSL
- Nicholas Casetti (Postgraduate Researcher) → PhD Student @ MIT
- Rebecca Neeser (MS 2022, ETH Zurich) → Intern @ VantAI
- 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 → Machine Learning Engineering @ Stealth
- 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