Bharath Ramsundar

Founder at deepforestsci

San Francisco Bay Area United States
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Summary

🤩
Rockstar
Bharath Ramsundar is the founder of Deep Forest Sciences and creator of DeepChem, a widely used open-source toolkit for applying deep learning to drug discovery, quantum chemistry, materials science, and biology. With a Stanford CS PhD focused on deep drug discovery and 14 years of experience, he blends rigorous research with hands-on engineering to push ML into real-world scientific problems. Based in the San Francisco Bay Area, he has authored technical books for O'Reilly and previously co-founded Computable, demonstrating both product and academic leadership. His GitHub contributions emphasize maintaining and improving DeepChem—cleaning code, fixing bugs, and experimenting with models like Atomic Conv—showing a preference for practical, reproducible scientific code. Colleagues describe him as a builder who bridges academic breakthroughs and developer-friendly tooling, making advanced methods accessible to practitioners. His background suggests a rare mix of entrepreneurial grit, deep domain expertise, and commitment to open science.
code14 years of coding experience
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Stackoverflow

Stats
21reputation
143reached
5answers
0questions
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Github Skills (12)

machine-learning10
tensorflow10
python10
data-science10
regression9
maintenance8
code-cleanup8
classification8
keras6
rdkit6
deep-learning6
jupyter-notebook6

Programming languages (15)

C++CSSRustCTeXGoHTMLJupyter Notebook

Github contributions (5)

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deepchem/deepchem

Sep 2015 - Sep 2022

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Role in this project:
userData Scientist & ML Engineer
Contributions:17 releases, 2245 reviews, 1676 commits in 7 years 1 month
Contributions summary:Bharath's commits primarily involve cleaning up and fixing bugs in the DeepChem codebase. The changes include cleaning up code, addressing bug fixes within existing code, and renaming a data featurizer. In addition, they are experimenting with and updating a variety of models, including one based on Atomic Conv and the testing of the effects of various loss function adjustments.
chemistrysciencedrug-discoverydeep-learningbiology
rbharath/rbharath.github.io

May 2016 - Nov 2020

Build a Jekyll blog in minutes, without touching the command line.
Contributions:4 reviews, 209 commits, 23 PRs in 4 years 6 months
jekyll-blogjekylljekyll-thememinutes
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