Vishal Siramshetty is a Principal Scientist based in South San Francisco with 12 years of experience applying cheminformatics and AI to computational drug discovery. Currently at Genentech after a postdoctoral stint at NCATS, he builds predictive models for biological activity, toxicity and ADME while translating findings into practical informatics workflows and KNIME tools. His background spans academia and industry—from PhD work in cheminformatics to building semantic-web and extraction tools at Fraunhofer and EMBL-EBI—highlighting strengths in data mining, open-source tooling, and pipeline automation. Notably, he has a track record of releasing reproducible software (e.g., VirtualSPARQLer, OSRAChem) that bridges literature mining with structured chemical knowledge, reflecting a rare blend of domain expertise and engineering discipline.
12 years of coding experience
5 years of employment as a software developer
Dr. rer. Nat. (PhD), Cheminformatics, Dr. rer. Nat. (PhD), Cheminformatics at Freie Universität Berlin
Master of Science (M.Sc.), Life Science Informatics, Master of Science (M.Sc.), Life Science Informatics at Rheinische Friedrich-Wilhelms-Universität Bonn / University of Bonn
Bachelor's degree, Pharmacy, Bachelor's degree, Pharmacy at Osmania University
The source code for ADME@NCATS application that hosts prediction models for ADME properties. Link to application: https://opendata.ncats.nih.gov/adme/home
Contributions:6 releases, 125 commits, 47 PRs in 2 years 6 months
Contributions:13 commits, 8 pushes in 4 years 10 months
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Vishal Siramshetty - Principal Scientist at Genentech