Amir Bahmani is an instructor and Director of the Stanford Deep Data Research Center with a PhD in Computer Science and nine years of professional experience focused on distributed and parallel computing applied to digital health. He leads efforts to improve scalability, interoperability, and security for large biomedical datasets and contributes to national initiatives like the VA Million Veteran Program and NIH Bridge2AI. At Stanford he has taught cloud computing for biology and healthcare and previously directed science & technology efforts at the Healthcare Innovation Lab, bridging research engineering with practical clinical data workflows. Passionate about equitable access, he seeks collaborations that advance nonprofit missions and serve underserved communities, and his background spans hands-on cloud-native implementations and academic leadership. A not-obvious detail: beyond strategy and teaching, he has deep experience building cloud-based annotation and bioinformatics pipelines from his Stanford internship and early HPC work, giving him both research depth and production engineering chops.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at North Carolina State University
Computer Science, Computer Science at Missouri University of Science and Technology
Swarm: A Federated Cloud Framework for Large-scale Variant Analysis: https://doi.org/10.1371/journal.pcbi.1008977
Contributions:17 commits, 15 PRs, 18 pushes in 2 years 11 months
doiswarmjournalvariant-analysisscale
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Amir Bahmani - Instructor at Stanford Deep Data Research Center