Machine Learning Researcher at Lomonosov Moscow State University (MSU)
Russia
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Summary
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Senior
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Top School
Vsevolod Shegolev is a machine learning researcher and computational biochemist with 8 years of experience applying ML and physics-based methods to molecular modeling and drug design. He has built enzyme models combining homology modeling, AlphaFold and molecular dynamics, established a consensus docking pipeline with strong correlation to experimental pIC50s, and designed ADMET-aware kinetics models for multiphase systems. His work spans custom force field development, large-scale subgraph/fingerprint searches across >10M compounds, and free-energy calculations via metadynamics and alchemical methods to guide inhibitor optimization. At BIOCAD he evaluated and containerized AiZynthFinder workflows and ran blinded A/B tests showing model-predicted retrosynthesis comparable to human chemists. Based in Russia and trained at MSU in computational chemistry and enzymology, he brings a rare blend of hands-on quantum/MD expertise and ML-driven pipeline engineering for translational drug discovery.
Contributions:10 releases, 31 PRs, 105 pushes in 1 year
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Vsevolod Shegolev - Machine Learning Researcher at Lomonosov Moscow State University (MSU)