Adit Shah is a research engineer in the San Francisco Bay Area with nine years of experience building ML systems for biomedical and climate-impact applications. Currently the first computational hire at Until, he leads ML for small-molecule cryoprotectant discovery and has built data platforms from scratch to support scientific workflows. His background spans AI-driven image analysis for drug discovery at the Broad Institute, brain-to-speech interfaces in an active clinical trial, and large-scale traffic-smoothing RL experiments that were deployed to 100 vehicles. Adit pairs rigorous EECS training from UC Berkeley with hands-on research fellowships (including a selective EPFL placement) and student leadership running a 30-person neurotech software team. He’s comfortable shipping production-ready tooling and publishing research, and often works at the intersection of few-shot learning, simulation-to-reality transfer, and real-world deployment.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS Electrical Engineering and Computer Sciences, Bachelor of Science - BS Electrical Engineering and Computer Sciences at University of California, Berkeley
A framework written in Kotlin for testing algorithms in a multi-node distributed system (e.g. drones). Provides an API for communication between nodes.
Contributions:14 PRs, 34 pushes, 10 branches in 7 months
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