Lee Lichtenstein is a Director of Computational Methods at the Broad Institute with 13 years of experience leading bioinformatics and backend engineering teams to production-quality genomic analysis tools. He combines deep technical leadership—shaped by roles at Broad, Amazon, and research institutes—with hands-on contributions to high-profile open-source projects like GATK, where he improved somatic CNV analysis, refactored core code, and built compatibility tools for legacy genomics workflows. Known for bridging research and production, he has repeatedly translated complex algorithms into scalable, auditable pipelines used by genomics labs and industry partners. His background spans applied science management and principal engineering, giving him a rare mix of strategic program leadership and day-to-day coding credibility. Based in Greater Boston, he holds advanced study from Boston University and undergraduate degrees from Cornell, and often focuses on pragmatic interoperability issues that accelerate adoption of new methods.
12 years of coding experience
23 years of employment as a software developer
Stuyvesant
Bachelor's degree, Bachelor's degree at Cornell University
Official code repository for GATK versions 4 and up
Role in this project:
Back-end Developer & Bioinformatics Engineer
Contributions:9 reviews, 257 commits, 95 PRs in 7 years
Contributions summary:Lee made extensive contributions to the GATK project, particularly focusing on the development and maintenance of somatic copy number variant (CNV) analysis tools. Their work involved refactoring code, improving the accuracy of CNV calls, and converting data formats for compatibility with various tools. They also contributed to the creation of a new CNV workflow, including the implementation of a tool for generating legacy format segments for IGV compatibility. This indicates a strong focus on bioinformatics and backend development within the context of genomic analysis.
Contributions:22 releases, 762 commits, 28 PRs in 5 years
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Lee Lichtenstein - Director, Computational Methods