Connor W. Coley
Associate Professor, Warren K. Lewis Professor in Chemical Engineering
Develops machine learning and generative AI for chemistry, including computer-aided retrosynthesis, reaction prediction, and synthesizable molecular design.
Connor W. Coley's lab at MIT works on proteins, drugs & materials, generative & foundation models and speech synthesis & voice. 83 papers since 2023, 13 at top venues, mostly Journal of Chemical Information and Modeling and ICLR. 20 PhD students. 58 alumni, most often to Amazon and Google. Applications close .
At a glance
- papers, 2023–2026
- 22/ year
- at T1 venues
- 16%
- PhD students
- 20
- MS students
- 0
- alumni listed
- 58
Papers by yearfrom the lab homepage, 2023–2026
- 14 papers2026 · T1 2 · collecting
- 22 papers2025 · T1 4
- 19 papers2024 · T1 2
- 28 papers2023 · T1 5
T1 venuesOtherVenues: Journal of Chemical Information and Modeling, ICLR, Nature, Cell, ICML
Research focuspaper titles that use each topic's words
- Proteins, drugs & materials19 papers
- Generative & foundation models11 papers
- Speech synthesis & voice8 papers
- computer-aided3 papers
- molecular design1 paper
Paper list
From the lab homepage.
202614 papers
- Nature CatalysisA geometric foundation model for enzyme retrieval with evolutionary insights (opens in a new tab)
- Chem. Sci.A machine learning-based workflow for transaminase selection (opens in a new tab)
- Chem. Soc. Rev.An overview of reaction outcome prediction with physics-based and data-driven methods (opens in a new tab)
- PLOS ONEComputational design of functional random heteropolymers through atomistic simulations (opens in a new tab)
- TMLR (T1)Efficient and Programmable Exploration of Synthesizable Chemical Space (opens in a new tab)
- PatternsEmmaEmb: A quantitative framework for analyzing embedding spaces in molecular biology (opens in a new tab)
- MacromoleculesEnergy Landscape and Stability in Random Heteropolymers: Somewhere Between Protein Folding and Plastic Miscibility (opens in a new tab)
- ICLR (T1)FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time (opens in a new tab)
- ACS Cent. Sci.Higher-level Strategies for Computer-Aided Retrosynthesis (opens in a new tab)
- Environ. Sci. Technol.Hydrolysis Reaction Rate Prediction Using Machine Learning: WaterDRoP (opens in a new tab)
- Journal of Chemical Information and ModelingPathway-Aware Template-Based Retrosynthesis (opens in a new tab)
- Nano Lett.Polymerized Short Sequences as a Template for Protein Folding and Evolution (opens in a new tab)
202522 papers
- Cell (T1)A generative deep learning approach to de novo antibiotic design (opens in a new tab)
- J. Am. Chem. Soc.Anomeric Selectivity of Glycosylations Through a Machine Learning Lens (opens in a new tab)
- J. Chem. Theory Comput.Anticipating the Selectivity of Cyclization Reaction Pathways with Neural Network Potentials (opens in a new tab)
- Found. Trends in MLArtificial intelligence for science: Quantum, atomistic, and continuum systems (opens in a new tab)
- Acc. Chem. Res.ASKCOS: an open source software suite for synthesis planning (opens in a new tab)
- MatterAutonomous discovery of functional random heteropolymer blends through evolutionary formulation optimization (opens in a new tab)
- Journal of Chemical Information and ModelingBatched Bayesian optimization by Maximizing the Probability of Including the Optimum (opens in a new tab)
- ACS Cent. Sci.Challenging Reaction Prediction Models to Generalize to Novel Chemistry (opens in a new tab)
- Journal of Chemical Information and ModelingChemprop v2: An Efficient, Modular Machine Learning Package for Chemical Property Prediction (opens in a new tab)
- Chem. SciData-Driven Recommendation of Agents, Temperature, and Equivalence Ratios for Organic Synthesis (opens in a new tab)
- Nat. Chem.Designing single-polymer-chain nanoparticles to mimic biomolecular hydration frustration (opens in a new tab)
- Nature (T1)Electron flow matching for generative reaction mechanism prediction (opens in a new tab)
202419 papers
- Syst. Des. Eng.A physics-inspired approach to the understanding of molecular representations and models (opens in a new tab)
- Nat. Comput. Sci.An algorithmic framework for synthetic cost-aware decision making in molecular design (opens in a new tab)
- Nat. Rev. Chem.Automation of air-free synthesis (opens in a new tab)
- An MIT Exploration of Generative AIClosing the execution gap in generative AI for chemicals and materials: freeways or safeguards (opens in a new tab)
- J. Chem. Phys.Comment on ‘Molecular hypergraph neural networks’ (opens in a new tab)
- J. Am. Chem. Soc.Data-efficient, chemistry-aware machine learning predictions of Diels-Alder reaction outcomes (opens in a new tab)
- Nat. Prod. Rep.Empowering natural product science with AI: leveraging multimodal data and knowledge graphs (opens in a new tab)
- Digital Discov.Extracting structured data from organic synthesis procedures using a fine-tuned large language model (opens in a new tab)
- Anal. Chem.Generating molecular fragmentation graphs with autoregressive neural networks (opens in a new tab)
- J. Am. Chem. Soc.Incorporating synthetic accessibility in drug design: Predicting reaction yields of Suzuki cross-couplings by leveraging AbbVie’s 15-year parallel library data set (opens in a new tab)
- ICLR (T1)Learning over molecular conformer ensembles: datasets and benchmarks (opens in a new tab)
- Journal of Chemical Information and ModelingMIST-CF: Chemical formula inference from tandem mass spectra (opens in a new tab)
202328 papers
- ACS Macro. Lett.A computationally informed unified view on the effect of polarity and sterics on the glass transition in vinyl-based polymer melts (opens in a new tab)
- Nat. Synth.A high-throughput platform for efficient exploration of functional polypeptides chemical space (opens in a new tab)
- MacromoleculesAdsorption of biomimetic amphiphilic heteropolymers onto graphene and its derivatives (opens in a new tab)
- EngineeringArtificial intelligence for retrosynthesis prediction (opens in a new tab)
- Chem. Eur. J.Combining molecular modeling and machine learning for accelerated reaction screening and discovery (opens in a new tab)
- AIChE J.Computer-aided evaluation and exploration of chemical spaces constrained by reaction pathways (opens in a new tab)
- PatternsComputer-aided multi-objective optimization in small molecule discovery (opens in a new tab)
- Journal of Chemical Information and ModelingData sharing in chemistry: Lessons learned and a case for mandating structured reaction data (opens in a new tab)
- ACS Cent. Sci.Dataset design for building models of chemical reactivity (opens in a new tab)
- Nature Communications (T1)Diversity-oriented synthesis encoded by deoxyoligonucleotides (opens in a new tab)
- Nat. Chem. Biol.DNA-encoded library (DEL)-enabled discovery of proximity-inducing small molecules (opens in a new tab)
- ICLR (T1)Equivariant shape-conditioned generation of 3D molecules for ligand-based drug design (opens in a new tab)
Where alumni went58 listed, 41% to industry
Industry 14Academia 20
Most often to
- Amazon
- Microsoft
Also to
- MIT
- Stanford University
- Caltech
Apply to MITFall 2027
MIT EECS Computer Science PhD
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