People

Group photo

February 2024

Principal Investigator

Connor W. Coley photo

Connor W. Coley

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.

Postdoctoral Associates & Fellows and Research Scientists

Babak Mahjour photo

Babak Mahjour

Postdoctoral Fellow

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 Levin photo

Itai Levin

Postdoctoral Associate

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 Joung photo

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.

Jordan Liles photo

Jordan Liles

Postdoctoral Associate

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 Wang photo

Runzhong Wang

Postdoctoral Associate

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.


Graduate Students

Alex Stoneman photo

Alex Stoneman

PhD Student

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 Zhang photo

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.

Herry (Tianyi) Jin photo

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.

Jenna Fromer photo

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.

Jihye Roh photo

Jihye Roh

PhD Student

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 Provenzano photo

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 photo

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.

Kento Abeywardane photo

Kento Abeywardane

PhD Student

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 Yu photo

Kevin Yu

SM Student

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 Lederbauer photo

Magdalena Lederbauer

Visiting Graduate Student

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 Xie photo

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.

Mrunali Manjrekar photo

Mrunali Manjrekar

PhD Student

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.

Nicholas Casetti photo

Nicholas Casetti

PhD Student

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 Raghavan photo

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.

Shitong Luo photo

Shitong Luo

PhD Student

Shitong received his B.S. in Data Science from Peking University. He is now a PhD student in Electrical Engineering and Computer Science (EECS) at MIT. He is interested in how to bridge the gap between machine learning and experiments.

Wenhao Gao photo

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 photo

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 photo

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.


Software Developers

Sourabh Choure photo

Sourabh Choure

Front-End Development

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 Fong photo

Mun Hong Fong

Back-End Development

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.

Huiqian Lin photo

Huiqian Lin

DevOps & Project Management

Huiqian Lin is an experienced full-stack engineer focusing on Kubernetes, Cloud DevOps and CICD pipeline. She is also an Agile project manager.


Undergraduate and Postgraduate Researchers

Alexandra Volkova photo

Alexandra Volkova

UROP @ MIT

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 Huang photo

Jonathan Huang

UROP @ MIT

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.

Montgomery Bohde photo

Montgomery Bohde

MSRP @ Texas A&M

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 Dassanayake photo

Ne Dassanayake

UROP @ MIT

Nicolas Manno photo

Nicolas Manno

UROP @ MIT

Ray Wang photo

Ray Wang

UROP @ MIT

Ray is a senior in 6-3(Math) and 18(Mathematics) at MIT. He is interested in using combinatorial algorithm and machine learing to improve mass-spectrum prediction model.

Lab Alumni

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