February 2024
Associate Professor (Without Tenure)
Class of 1957 Career Development Professor
Department of Chemical Engineering
Department of Electrical Engineering and Computer Science
Connor W. Coley is the Class of 1957 Career Development Professor and an Associate Professor without tenure 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 works at the interface of chemistry and data science to develop models that understand how molecules behave, interact, and react and use that knowledge to engineer new ones, with an emphasis on therapeutic discovery. Connor is a recipient of C&EN’s “Talented Twelve” award, Forbes Magazine’s “30 Under 30” for Healthcare, Technology Review’s 35 Innovators Under 35, the NSF CAREER award, the ACS COMP OpenEye Outstanding Junior Faculty Award, the Bayer Early Excellence in Science Award, the 3M NTFA, and was named a Schmidt AI2050 Early Career Fellow, a 2023 Samsung AI Researcher of the Year, and a Scialog Fellow (Automating Chemical Laboratories). Connor has been recognized for his teaching and mentorship by MIT’s inaugural Common Ground Award for Excellence in Teaching, the 2024 Outstanding UROP Mentor Award, and the 2024 James W. Swan Outstanding Faculty Award for Graduate Teaching in Chemical Engineering.
Babak completed his PhD in medicinal chemistry with Prof. Tim Cernak at the University of Michigan in 2023. He joined the Coley group soon after to continue studying chemical synthesis and lab automation, with an eye towards AI-driven translational research.
Itai received his B.A. in Chemistry and Chemical Biology from Cornell and his PhD 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.
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.
Jordan completed his Ph.D. in Organic Chemistry in 2024 with Matthew Sigman at the University of Utah. Shortly after, he joined the Coley group to pursue machine learning-enabled approaches to catalyst design and automation-assisted reaction optimization. He is interested in developing ML tools rooted in physical organic chemistry principles to drive new reaction discovery and develop new asymmetric methods.
Runzhong received his PhD in Computer Science at Shanghai Jiao Tong University in the summer of 2023. He joined the Coley Research Group shortly afterward. He is interested in the intersected topics of machine learning and combinatorial optimization, and their applications in computational metabolomics.
Alex received his B.E. in Chemical Engineering and Chemistry from Vanderbilt University in 2023. As a Chemical Engineering PhD student at MIT, co-advised by Paula Hammond, he is interested in using high-throughput experimentation and machine learning to improve nanoparticle-based cancer treatments.
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.
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.
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.
Jihye received her BS in Chemical and Biological Engineering from Seoul National University in 2022 and is now a PhD student at MIT in Chemical Engineering. She is interested in developing computer-aided multistep retrosynthesis models for complex molecules.
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 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.
Kento received a B.S. in Chemical Engineering and an M.S. in Data-Enabled Computational Engineering and Sciences from Brown University. He joined the group in 2024 as a PhD student in Chemical Engineering and Computation at MIT and his research interest is in 3D ligand-based drug design using AI/ML.
Kevin received his BS in Chemistry and CS from Caltech in 2022 and is now an SM student at MIT in Computational Science and Engineering. He is broadly interested in developing predictive tools and algorithms that can benefit synthetic chemists, with a focus on synthesis planning for complex molecules.
Magdalena received her BSc in Chemistry from ETH Zurich and is finishing her MSc in Chemistry at ETH Zurich. She previously worked on Large Language Model agents in heterogeneous catalysis at EPFL and is currently interested in using machine learning for structure elucidation and spectroscopy.
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.
Mrunali received her B.S. in Bioengineering and Electrical Engineering and Computer Sciences (EECS) from the University of California, Berkeley in 2023, and is now a PhD student in Computational and Systems Biology at MIT. She is interested in developing machine learning methods for small-molecule discovery and generation by leveraging mass spectra.
Nick received his BS in Chemical Engineering from Purdue University in 2022, and is now a PhD student in Chemical Engineering at MIT. He is interested in using machine learning for reaction mechanism elucidation and discovery.
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 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 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 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.
Sourabh holds an M.S. in Computer Science from UT Dallas, with a specialization in Distributed Systems. His passion for scalable computing drove him to the Meta Ads team, where he developed tools to filter ads based on sensitive category data across Facebook apps. Currently, he is a Software Engineer at MIT, working with the MLPDS Consortium, where he focuses on building and improving the ASKCOS platform.
Mun Hong graduated from Purdue University with B.S. in Computer Science, minor in Chemistry. He is interested in generative modeling, synthesis planning, and reaction outcome prediction.
Alexandra is a junior studying Computer Science and Molecular Biollogy (6-7) and Finance (15-3) at MIT. She is interested in advancing drug design through intelligent selection of drug candidates for synthesis.
Jonathan is an senior in EECS (6-2) and Biology (7) at MIT. He is interested in applying optimization techniques to efficiently explore combinatorial synthesis drug libraries.
Graduate students, postdoctoral associates & fellows, research scientists
Qianxiang Ai (Research Scientist) → Research Scientist @ Abstrax Tech
Samuel Goldman (PhD 2024, MIT) → Associate @ MPM BioImpact
Guangqi Wu (Postdoctoral Associate) → Marie Skłodowska-Curie Fellow @ Oxford University
Fanwang Meng (Postdoctoral Associate) → Banting Fellow @ Queens University
John Bradshaw (Postdoctoral Associate) → TBA
Natasha Faurschou (Visiting PhD Student, University of Copenhagen) → PhD Student @ University of Copenhagen
David Graff (PhD 2023, MIT) → ML Scientist @ Atomwise
Christian Ulmer (MS 2023, KTH) → Software Engineer @ Scandens
Rocío Mercado (Postdoctoral Associate) → Assistant Professor @ Chalmers
Thijs Stuyver (Postdoctoral Associate) → Assistant Professor @ Université PSL
Nicholas Casetti (Postgraduate Researcher) → PhD Student @ MIT
Rebecca Neeser (MS 2022, ETH Zurich) → Intern @ VantAI → PhD student @ EPFL
Matteo Aldeghi (Research Scientist) → Senior Research Scientist @ Google Research → Director of Machine Learning Research @ Bayer
Aparajita Dasgupta (Postdoctoral Associate) → Senior Scientist, Process Development @ Pfizer
Undergraduate students
Ron Shprints (UG 2025, MIT) → UROP @ Kaiming He
Juncheng (Tony) Lu (UG, CMU)
Giselle Brown (UG 2025, UCLA)
Ghazal Mirzazadeh (UG, Georgia Tech)
Collin Lung (UG, MIT)
Alec Zhu (UG, MIT)
Vlad Cherdantsev (UG, MIT)
Lucas Abounader (UG 2024, Caltech) → Fulbright Fellow @ University of Padova
Pragnay Nevatia (UG 2024, UC Berkeley) → PhD Student @ MIT
Anjolaoluwa Fayemi (UG 2026, MIT)
Sabrina Cai (UG 2024, MIT)
Jiayi Xin (UG 2024, HKU/Wellesley) → PhD Student @ UPenn
Saul A. Vega Sauceda (UG 2024, MIT)
Janet Li (UG 2023, Harvard) → Software Engineer Intern @ Microsoft
Divya Nori (UG 2025, MIT) → Intern @ D.E. Shaw Research
Chanwoo Yoon (UG 2025, MIT)
Katherine Lim (UG 2023, MIT)
Jacob Yasonik (UG 2024, MIT) → Machine Learning Engineer @ Osmo
Min Htoo Lin (UG 2021, Nanyang Technological University) → AI Engineer @ Talo Labs
Tyra Jones (UG 2021, Spelman College & UG 2023, Georgia Tech)
Jackson Burns (UG 2022, University of Delaware) → PhD Student @ MIT