Ashis Saha is a Computational Scientist with 12 years of experience who transforms large-scale genomics and clinical datasets into actionable insights to accelerate drug discovery and safety assessment. At Genentech he builds integrative multi-omics pipelines for therapeutic target prioritization and analyzes clinical trial genomics—including HLA, PRS, and variant associations—to understand immunotherapy response and adverse events. His PhD work at Johns Hopkins produced robust methods for eQTL, co-expression, and trans-eQTL analysis used in consortia like GTEx and eQTLGen, reflecting a strong foundation in reproducible, large-scale regulatory genomics. Comfortable bridging academic rigor and product-focused engineering, he pairs bioinformatics and AI/ML expertise with production-grade pipeline development. Based in South San Francisco, he brings both biological insight and software engineering discipline to biomarker discovery in oncology and autoimmune diseases. An often-overlooked strength is his track record of establishing best-practice workflows that reduce false positives in complex genetic analyses.
12 years of coding experience
7 years of employment as a software developer
Johns Hopkins University
Master of Science (M.S.), Computer Engineering, Master of Science (M.S.), Computer Engineering at Korea University
B.Sc., Computer Science & Engineering, B.Sc., Computer Science & Engineering at Bangladesh University of Engineering and Technology
Contributions:2 PRs, 6 pushes, 1 branch in 3 years
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