Chris Whelan
Senior Computational Biologist
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolChris Whelan is a Senior Computational Biologist at the Broad Institute with 13 years of experience applying distributed computing and machine learning to genomics. He leads development of structural variation and cell-free DNA analysis methods in GATK, designing scalable Spark-enabled tools and fixing challenging serialization and parallelization issues in a widely used open-source toolkit. With a PhD in computer science, he bridges deep algorithmic expertise and production engineering—building clinically minded variant-calling pipelines for prenatal genetics and large-scale population studies. His background as a senior software engineer gives him rare fluency across web, HPC, and cloud platforms (Java, Scala, Python, GCP, WDL/Cromwell). He focuses on hard-to-access genomic regions and the mechanisms that create structural variants, translating complex biology into robust, interpretable calls for research and clinical use. Based in Boston, he combines academic publishing with hands-on contributions to the core GATK codebase used across the genomics community.
13 years of coding experience
11 years of employment as a software developer
BA, Computer Science, BA, Computer Science at Harvard UniversityPhD (Expected November 2013), Computer Science, PhD (Expected November 2013), Computer Science at OHSU
Github Skills (11)
bioinformatics10
javas10
spark10
gatk10
java10
genomes9
genomics9
genome9
data-serialization8
excel-dna8
serialization8
Programming languages (9)
Github contributions (5)
broadinstitute/gatk
Nov 2015 - Jul 2021
Official code repository for GATK versions 4 and up
Role in this project:
Back-end Developer
Back-end DeveloperContributions:53 reviews, 312 commits, 69 PRs in 5 years 9 months
Contributions summary:Chris contributed significantly to the development of new Spark tools within the GATK framework for structural variant analysis. Their work involved implementing new tools to identify potential structural variant breakpoints and generate data for local assemblies. This included coding in Java and utilizing Spark for parallel processing. The user also fixed serialization issues within the system.
genomesciencednaspark-mlngs
broadinstitute/gatk-sv-single-sample
Sep 2019 - Nov 2020
WDLs for the Clinical GATK-SV pipeline
Contributions:9 releases, 46 commits, 31 PRs in 1 year 2 months
gatkbioinformaticspipelineclinical
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