People

Group photo

September 2025

Principal Investigator

Connor W. Coley photo

Connor W. Coley

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.

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.

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.

Jonas Rein photo

Jonas Rein

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.

Justin Bui photo

Justin Bui

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.


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.

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.

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. His research interest is in 3D drug design using AI/ML.

Kevin Yu photo

Kevin Yu

PhD Student

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 Cox photo

Matthew Cox

PhD Student

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 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.

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.

Suong Tran photo

Suong Tran

PhD Student

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 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.

Zahmiria Johnson photo

Zahmiria Johnson

PhD Student

Zahmiria graduated from UC Berkeley in 2024 with a B.S. in Chemical Engineering. As a PhD student at MIT in Chemical Engineering co-advised by Katie Galloway, they are interested in bio-applied automation and small molecule control of synthetic biology circuits.

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

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.

Samuel Gong photo

Samuel Gong

Front-End Development

Samuel Gong is a full-stack engineer specializing in modern JavaScript frameworks, with expertise in responsive UI, end-to-end testing, and performance optimization.


Undergraduate and Postgraduate Researchers

Alexandra Volkova photo

Alexandra Volkova

UROP @ MIT

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 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.

Nathan Leung photo

Nathan Leung

UROP @ MIT

Nathan is a freshman studying EECS (6-5) at MIT. He is interested in exploring concepts in chemical informatics and machine learning through projects in devices and instrument automation.

Ne Dassanayake photo

Ne Dassanayake

UROP @ MIT

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 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 algorithms and machine learning to improve mass-spectrum prediction models.

Sarah Cao photo

Sarah Cao

UROP @ MIT

Sarah studies Chemistry-Biology and Math with CS at MIT! She is interested in using generative models to navigate the chemical space through individual mechanistic steps.

Greycen Ren photo

Greycen Ren

UROP @ MIT

Greycen is a senior in 6-7 and 18 at MIT. He’s interested in computational methods with applications in biology and chemistry.

Janet Guo photo

Janet Guo

UROP @ MIT

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.

Phoenix Wu photo

Phoenix Wu

UROP @ MIT

Phoenix is a junior in 6-4 (AI and Decision Making) at MIT. He is interested in developing computer aided synthesis planning tools for organic chemistry.

Gozel Dovranova photo

Gozel Dovranova

UROP @ MIT

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 Leung photo

Kasie Leung

UROP @ Harvard

Kasie is a junior at Harvard, studying Chemistry & Physics and Computer Science. She is interested in developing data-driven tools to predict electrochemical reactivity.

Aquila Wolff photo

Aquila Wolff

UROP @ Harvard

Aquila is a junior studying Chemistry and Physics at Harvard. His main interests are synthesis route design and reaction prediction through computational methods.

Ali Alsaleh photo

Ali Alsaleh

UROP @ MIT

Ali is a sophomore at MIT studying Chemistry (5). He is interested in exploring applications of lab automation in chemical discovery.

Hasan Alkhalifa photo

Hasan Alkhalifa

UROP @ MIT

Hasan Alkhalifa is a sophomore majoring in Chemical Engineering (10). He is passionate about integrating machine learning with chemical research to accelerate the design of pharmaceuticals and catalysts, aiming to bridge data-driven methods with experimental innovation.

Lab Alumni

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