Machine Learning Research Scientist at Arc Institute
San Francisco Bay Area United States
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Summary
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Rockstar
🎓
Top School
Abhinav Adduri is a Machine Learning Tech Lead in the Bay Area with 11 years of experience building ML-driven systems that bridge biology and software. He trains foundation models of cellular state and function, translating sequence data into actionable molecular insights and helping discover novel therapeutics during his PhD—work that produced a validated antifungal, Edaphochelin A. Prior roles span research fellowships and industry internships where he improved production ML systems (ETA and fraud models) and implemented distributed caches and frontend features for high-profile open-source projects like Firefox Send. He combines deep academic rigor from a CMU PhD and dual BAs from UC Berkeley in CS and Biochemistry with hands-on engineering across full-stack, ML research, and product delivery. Known for shipping both research breakthroughs and polished user-facing features, he thrives at the intersection of biology, models, and production software. He also brings a rare mix of wet‑lab-informed intuition and frontend/backend engineering fluency that speeds translation from idea to validated result.
11 years of coding experience
1 year of employment as a software developer
Bachelor of Arts (B.A.), Computer Science, Bachelor of Arts (B.A.), Computer Science at University of California, Berkeley
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Carnegie Mellon University
Simple, private file sharing from the makers of Firefox
Role in this project:
Full-stack Developer
Contributions:166 commits, 56 PRs, 152 pushes in 2 months
Contributions summary:Abhinav primarily contributed to the frontend of the project, focusing on implementing the user interface and download functionality. They updated the JavaScript code by incorporating new functions for handling downloads. The commits demonstrate modifications to the existing HTML file and included new JavaScript files that added features such as file uploads and progress indicators. These changes are consistent with front-end development tasks, including UI/UX, and API interactions.
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Abhinav Adduri - Machine Learning Research Scientist at Arc Institute