Yanfei Guan
Cheminformatics Lead, AI ML Scientist
Cambridge, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolYanfei Guan is a cheminformatics lead and AI/ML scientist in Cambridge, MA with eight years of experience bridging computational chemistry and machine learning for drug discovery. She progressed from doctoral research and postdoctoral roles focused on automated workflows and molecular property prediction to senior R&D positions at Pfizer and now leads cheminformatics at Takeda, translating ML models into practical pharma discovery tools. Her background combines a PhD in Chemistry with applied mathematics from Shanghai Jiao Tong University, reflecting strong quantitative foundations alongside domain expertise in catalysis, synthesis prediction, and high-throughput computational pipelines. Notably, she has moved between academia and industry to operationalize research-grade algorithms at scale, making her especially skilled at turning complex quantum-chemical and ML methods into deployable discovery workflows.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Chemistry, Doctor of Philosophy - PhD, Chemistry at Texas A&M UniversityBachelor's degree, Chemistry & Applied Mathematics, Bachelor's degree, Chemistry & Applied Mathematics at Shanghai Jiao Tong University
Github Skills (42)
molecule10
drug-discovery10
chemistry10
message-passing10
gaussian10
prediction10
proteins10
temperature10
predict9
machine-learning9
harmonic9
substitution9
calculation9
deep-learning8
binding8
Programming languages (6)
Github contributions (5)
yanfeiguan/reactivity_predictions_substitution
Jun 2020 - May 2021
Platforms to predict reactivity for substitution reactions.
Contributions:31 commits, 2 PRs, 17 pushes in 10 months
substitutionplatformsreactivitypredictreactions
yanfeiguan/chemprop-atom-bond
Jan 2020 - Dec 2020
Message Passing Neural Networks for Molecule Property Prediction
Contributions:58 commits, 51 pushes, 2 branches in 10 months
property-predictionpredictiondeep-learningneural-message-passingmolecule
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