September 2025
Associate Professor
Class of 1957 Career Development Professor
Department of Chemical Engineering
Department of Electrical Engineering and Computer Science
Schwarzman College of Computing
Massachusetts Institute of Technology
Connor W. Coley is the Class of 1957 Career Development Professor and an Associate Professor at MIT in the Department of Chemical Engineering and the Department of Electrical Engineering and Computer Science. His research group works at the interface of AI and chemistry 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. He received his B.S. in Chemical Engineering from Caltech and his Ph.D. from MIT, followed by postdoctoral training at the Broad Institute.
Connor’s work has been recognized with the NSF CAREER Award (2021), C&EN’s “Talented Twelve” (2018), Forbes 30 Under 30: Healthcare (2019), Technology Review’s 35 Innovators Under 35 (2023), and the Bayer Early Excellence in Science Award (2021), among other honors. He was named as a Schmidt AI2050 Early Career Fellow (2022), Samsung AI Researcher of the Year (2023), Scialog Fellow (2024), and Camille Dreyfus Teacher-Scholar (2025), and was selected for the NAE Frontiers of Engineering Symposium (2025). Connor has been further recognized for his teaching and mentorship by MIT’s inaugural Common Ground Award for Excellence in Teaching (2023), the Outstanding UROP Mentor Award (2024), and the James W. Swan Outstanding Faculty Award for Graduate Teaching in Chemical Engineering (2024, 2025).
Outside of MIT, Connor is a scientific advisor to several companies pursuing AI-driven discovery. He serves on the advisory boards of ACS Central Science, Chemical Science, and Digital Discovery, and is an Associate Editor of the Journal of the American Chemical Society.
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.
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.
Postdoctoral Fellow (co-advised with Prof. Masha Elkin)
Jonas completed his PhD in Organic Chemistry at Cornell University with Prof. Song Lin in 2024. His postdoctoral research seeks to integrate organic chemistry with data-driven approaches to systematically identify gaps in the current landscape of organic synthesis and accelerate the discovery of innovative solutions in the laboratory.
Postdoctoral Fellow (co-advised with Prof. Klavs Jensen)
Justin received his Ph.D. in Chemical Engineering from UC Berkeley in 2024, working with Dr. Adam Weber and Prof. Alexis Bell to develop continuum models of electro-membrane and electrocatalytic systems. Afterwards, he worked at Caltech as a postdoc with Prof. Karthish Manthiram to develop flow reactors for electrochemical ammonia and epoxide synthesis. At MIT, Justin plans to leverage ML tools and automation to identify and optimize organic reactions that can be performed electrochemically.
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.
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.
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. His research interest is in 3D drug design using AI/ML.
Kevin received his BS in Chemistry and CS from Caltech in 2022 and an SM in Computational Science and Engineering from MIT. He is now a PhD student at MIT in Electrical Engineering and Computer Science. In addition to predictive chemistry methods, especially for synthesis planning, he is interested in how machine learning and cheminformatics can be leveraged for generating scientific insight or accelerating reaction discovery and development.
Matthew obtained his BS in Chemical Engineering from Caltech in 2024 and is now a PhD student in Chemical Engineering at MIT. He is interested in developing optimization and machine learning methods in the context of molecular design and discovery.
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.
Suong earned her BS in Chemistry and Data Analytics from Dickinson College in 2024. She is currently pursuing a PhD in Chemistry at MIT, with a focus on applying machine learning and data-driven approaches to synthesis planning.
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.
Huiqian Lin is an experienced full-stack engineer focusing on Kubernetes, Cloud DevOps and CICD pipeline. She is also an Agile project manager.
Alexandra is a junior studying Computer Science and Molecular Biology (6-7) and Finance (15-3) at MIT. She is interested in advancing drug design through intelligent selection of drug candidates for synthesis.
Montgomery is studying Computer Science and Applied Math at Texas A&M University (B.S. 2026), where he is advised by Prof. Shuiwang Ji. His research interest is in graph neural networks and genenerative models with applications in AI for Science.
Ne is a senior studying 6-3 and 8 at MIT. He is interested in the application of generative modeling to both drug design and reaction mechanisms.
Ray is a senior in 6-3 (Math) and 18 (Mathematics) at MIT. He is interested in using combinatorial algorithms and machine learning to improve mass-spectrum prediction models.
Greycen is a senior in 6-7 and 18 at MIT. He’s interested in computational methods with applications in biology and chemistry.
Janet is a junior majoring in 6-4 (AI and Decision Making) and minoring in 7 (Biology) at MIT. She is interested in developing automated workflows for conditional generation of small molecules.
Gozel is a senior double majoring in 10 (Chemical Engineering) and 6-4 (AI and Decision Making). She is interested in the application of machine learning to synthesis prediction in organic chemistry.
Kasie is a junior at Harvard, studying Chemistry & Physics and Computer Science. She is interested in developing data-driven tools to predict electrochemical reactivity.
Ali is a sophomore at MIT studying Chemistry (5). He is interested in exploring applications of lab automation in chemical discovery.
Graduate students, postdoctoral associates & fellows, research scientists
Priyanka Raghavan (PhD 2025, MIT) → Senior Scientist I, Computational Drug Discovery @ AbbVie
Mun Hong Fong (Software Developer, MIT) → PhD Student @ Duke
Herry (Tianyi) Jin (PhD 2025, MIT) → Postdoctoral Associate @ Caltech
Wenhao Gao (PhD 2025, MIT) → Postdoctoral Associate @ Stanford
Sourabh Choure (Software Developer, MIT) → Software Development Engineer @ Amazon Web Services (AWS)
Magdalena Lederbauer (MS 2025, ETH Zurich) → Visiting ML Scientist for Chemistry @ Entalpic
Keir Adams (PhD 2025, MIT) → ML Research Engineer @ D.E. Shaw Research
Joonyoung Joung (Posdoctoral Associate) → Assistant Professor @ Kookmin University
Itai Levin (PhD 2024, MIT BE) → Co-Founder @ Decycle Bio
Qianxiang Ai (Research Scientist) → Research Scientist @ Abstrax Tech
Samuel Goldman (PhD 2024, MIT CSB) → 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) → ML Scientist @ Prescient Design, Genentech
Natasha Faurschou (Visiting PhD Student, University of Copenhagen) → PhD Student @ University of Copenhagen
David Graff (PhD 2023, Harvard CCB) → ML Scientist @ Atomwise → ML Scientist @ Prescient Design, Genentech
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
Juncheng Lu (C-CAS Visiting Scholar @ MIT) → Senior @ CMU
Undergraduate students
Jonathan Huang (UG 2025, MIT)
Nicolas Manno (UG 2025, MIT)
Ron Shprints (UG 2025, MIT) → UROP @ Kaiming He
Juncheng (Tony) Lu (UG, CMU)
Giselle Brown (UG 2025, UCLA)
Joy Zhuo (UG, MIT)
Michael Dennison (UG, MIT)
Parker McClain (UG, MIT)
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
