Anish Athalye
Director, AI Research at Handshake
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAnish Athalye is a San Francisco–based AI and systems engineer with 13 years of experience bridging research and product—co-founder and former CTO of Cleanlab and now Director of AI Research at Handshake. He holds advanced degrees from MIT (SB, MEng, PhD) and has interned at OpenAI, Dropbox, and Google, blending rigorous academic depth with practical engineering. Anish is a prolific open-source maintainer and contributor, from system-level work on xv6 and dotfiles to ML tooling and popular educational projects like The Missing Semester. His contributions span full-stack development, ML engineering, and devops, and include hands-on work improving model-centered labs and production-focused data-quality tooling. Notably, he built user-facing utilities (lumen auto-brightness, git-remote-dropbox) that combine careful systems optimization with polished UX—reflecting a rare mix of low-level systems skill and product sensibility.
13 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Massachusetts Institute of Technology
Github Skills (86)
page-layout10
opencv10
custom-theme10
python10
beamer10
image-processing10
testing10
command-line-interface10
c1110
c1710
vim10
website-design10
flask10
operating-system10
customizer10
Programming languages (31)
Github contributions (5)
anishathalye/dotfiles
Jul 2013 - Jan 2023
~anish • powered by https://github.com/anishathalye/dotbot 💾
Role in this project:
DevOps Engineer
DevOps EngineerContributions:802 commits, 4 PRs, 456 pushes in 9 years 7 months
Contributions summary:Anish primarily focused on configuring and maintaining the project's environment. They added configurations for various tools like Vim, tmux, zsh, git, and rtorrent, creating a customized development environment. Furthermore, the user automated the installation process by creating a Python script and updated it for better robustness, showing a focus on improving the developer experience.
dotbot
anishathalye/lumen
Apr 2015 - Oct 2021
Magic auto brightness based on screen contents 💡
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:5 releases, 57 commits, 5 PRs in 6 years 7 months
Contributions summary:Anish primarily contributed to the implementation and optimization of the `lumen` application, which appears to be designed for automatic brightness control on macOS. They focused on core functionality, including gathering screen content data, computing brightness levels, and controlling the display brightness. The user optimized the brightness calculation process to reduce CPU usage and integrated a model-based approach to learn and adapt to user preferences for screen brightness. The user also introduced and enhanced the integration with macOS's brightness control features.
statusbarscreen-onbacklightmagicgamma
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