Karan Shukla is a software engineer with a decade of experience building AI tooling, transparency, and infrastructure for top tech companies across San Francisco. He has led Model Transparency Tooling at Google and drove system-level AI transparency and provenance efforts at Meta, shipping AI System Cards across 20+ product surfaces and prototyping C2PA provenance ingestion that influenced company-wide commitments. Comfortable across Python and JavaScript, Karan contributes to open-source ML interpretability work such as TensorFlow's TCAV, where he added proto-formatted outputs and Relative TCAV support. Currently focused on Chrome AI memory, context, and personalization, he pairs technical leadership with cross-functional execution—bridging product, UX, internationalization, and policy to operationalize responsible AI.
10 years of coding experience
4 years of employment as a software developer
Bachelor of Science (B.S.) Computer Science, Bachelor of Science (B.S.) Computer Science at The University of Texas at Dallas
Contributions:15 commits, 9 PRs, 11 comments in 1 month
Contributions summary:Karan implemented features related to TCAV (Testing with Concept Activation Vectors) interpretability project. They modified the codebase to return TCAV results in a proto format, adding a new `return_proto` argument to the `TCAV.run()` method and modifying several files, including `utils.py`, `tcav.py`, and `results.proto`, and added the `target_class` int. In addition, they updated the `results.proto` to include CAVaccuracies. Furthermore, they added support for Relative TCAV.
Contributions:27 pushes, 1 branch in 5 years 11 months
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