David Benjamin is a computational biologist and machine learning scientist with 11 years of experience translating complex genomic data into robust mutation-detection models at the Broad Institute. Trained as a physicist (PhD, Harvard) with a BS in Physics and Mathematics, he brings a rare blend of probabilistic modeling, deep learning and algorithmic rigor to bioinformatics problems. At Broad he has contributed to the flagship GATK repository, improving somatic variant likelihood estimation, contamination filtering, and performance/correctness of core pipelines. He enjoys mentoring and teaching—skills honed as a longtime instructor—and thrives on explaining technical ideas to diverse audiences. Colleagues describe him as collaborative and creative, and he’s equally comfortable prototyping research ideas and hardening them for production use.
11 years of coding experience
7 years of employment as a software developer
BS, Physics, Mathematics, BS, Physics, Mathematics at University of Michigan
Doctor of Philosophy (Ph.D.), Theoretical Condensed Matter Physics, Doctor of Philosophy (Ph.D.), Theoretical Condensed Matter Physics at Harvard University
Official code repository for GATK versions 4 and up
Role in this project:
Back-end Developer & Data Scientist
Contributions:207 reviews, 597 commits, 610 PRs in 7 years 8 months
Contributions summary:David implemented and refined methods for somatic variant analysis within a bioinformatics repository. Their contributions include the development of methods to estimate the accuracy of the likelihood calculations, the creation of a contamination model used for filtering, and the incorporation of various improvements, such as changes to the format of header fields. The user also made various performance and correctness improvements.
Contributions:1 review, 158 PRs, 804 pushes in 8 months
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