Shreyas Vinaya
AI Research Scientist at Mstack AI
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolShreyas Vinaya is an AI research scientist with nine years of experience and a focused three-plus year track record in applied machine learning, especially at the intersection of NLP, molecular design, and chemistry. Currently based in Bengaluru, he develops molecule generation algorithms and molecular LLM infrastructure—work that spans industry and top labs, including roles at Mstack AI, Yale, Harvard Medical School, and Deep Forest Sciences. He has practical experience migrating open-source drug-discovery tooling (DeepChem) from TensorFlow to PyTorch and improving its documentation, helping broaden its user base and accessibility. His background combines a CS undergraduate and an MS in Chemistry from BITS Pilani campuses, enabling him to bridge computational methods with domain chemistry in ways that accelerate retrosynthesis and materials discovery. Notably, he has translated ML research into prize-winning applied innovation and production-ready tooling, reflecting a bias toward reproducible, user-friendly research engineering.
9 years of coding experience
2 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and ScienceHigh School Diploma, Computer Science, High School Diploma, Computer Science at Sri Kumaran Children's Home - CBSEMaster of Science - MS, Chemistry, Master of Science - MS, Chemistry at Birla Institute of Technology and Science, Pilani - Goa Campus
English, Kannada, Hindi, Sanskrit
Github Skills (6)
documentation10
python5
deep-learning3
quantum-chemistry3
biology3
drug-discovery3
Programming languages (10)
Github contributions (5)
deepchem/deepchem
Apr 2023 - Mar 2026
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Role in this project:
Technical Writer
Technical WriterContributions:135 reviews, 63 PRs, 9 pushes in 2 years 11 months
Contributions summary:Shreyas's commits primarily focused on updating and cleaning the documentation for the `BasicMolGANModel` within the `deepchem` repository. These changes involved fixing formatting issues, clarifying explanations of model functionality, and improving the overall presentation of the documentation. The contributions aimed to enhance the clarity and readability of the model's documentation for users.
deep-learningquantum-chemistrydrug-discoverybiologymaterials-science
deepforestsci/DeepRetro
Jul 2025 - Jul 2026
Recursive LLMs for Retrosynthesis
Contributions:19 reviews, 16 PRs, 63 pushes in 1 year
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.