Shahab Sarmashghi is a postdoctoral scientist at the Broad Institute and affiliated research fellow at Harvard Medical School and Dana-Farber, applying statistical, algorithmic and mathematical frameworks to decode cancer genome rearrangements and mechanisms of therapy resistance. With eight years of experience and a PhD in Electrical and Computer Engineering from UC San Diego, he builds scalable methods for high-throughput sequencing analysis that span applications from tumor evolution to ecosystem biodiversity and food safety. His work blends rigorous modeling of genomic overlap, assembly-free analysis of low-coverage WGS, and large-scale model training across hundreds of species, enabling robust inference from noisy or sparse data. Notably, he moves comfortably between algorithm development and practical pipelines—simulating dynamic populations, estimating genome repeat content, and integrating pathology and expression data for translational cancer studies.
8 years of coding experience
6 years of employment as a software developer
University of California San Diego
Bachelor of Science (BSc), Electrical Engineering, Bachelor of Science (BSc), Electrical Engineering at Sharif University of Technology
Contributions:7 releases, 23 commits, 26 pushes in 2 years 1 month
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