Shagun Sodhani

Staff Research Scientist at Google DeepMind

India
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Summary

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Shagun Sodhani is a Staff Research Scientist with 13 years of experience bridging machine learning research and production-grade software engineering, currently at Google DeepMind after leading AI research efforts at Meta. He has co-led initiatives on autonomous research agents, trained foundation models for adaptive neural interfaces, and contributed to 10+ top-tier publications across representation learning, lifelong learning, and RL. A seasoned open-source contributor, he fixed core bugs and built an Ax hyperparameter optimization plugin for Facebook Research’s Hydra, improving experiment configuration and reproducibility. Trained at MILA under Yoshua Bengio and with industry stints at Adobe and Microsoft Research, he pairs deep academic grounding with practical product and tooling impact. Known for mentoring teams and shipping ML toolkits, he often focuses on making complex research workflows robust and automatable.
code13 years of coding experience
job13 years of employment as a software developer
bookMasters Artificial Intelligence, Masters Artificial Intelligence at Université de Montréal
bookIndian Institute of Technology Roorkee
bookHigh School High School/Secondary Diplomas and Certificates, High School High School/Secondary Diplomas and Certificates at Somerville School
languagesEnglish, Hindi
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Stackoverflow

Stats
21reputation
164reached
0answers
1question
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Github Skills (6)

configuration-management10
python10
pytest9
testing9
php6
gd6

Programming languages (16)

JavaCSSC++CScalaTeXHTMLJupyter Notebook

Github contributions (5)

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hydra-ecosystem/hydra

Jan 2020 - Feb 2021

Hydra is a framework for elegantly configuring complex applications
Role in this project:
userBack-end Developer
Contributions:128 reviews, 78 commits, 129 PRs in 1 year 1 month
Contributions summary:Shagun primarily contributed to the `facebookresearch/hydra` repository by fixing bugs related to the `utils.instantiate()` function, ensuring it correctly handles interpolated values. They also developed a plugin to integrate the Ax hyperparameter optimization platform with Hydra, streamlining the experimentation process. Further, they implemented improvements to testing and logging of the Ax plugin.
pytorch-lightningcomplex-applicationsframeworkhydra
shagunsodhani/spatium-v1

Nov 2014 - Nov 2018

Contributions:184 commits, 48 pushes, 1 branch in 4 years
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