Laura Gauthier
Senior Computational Biologist
Arlington, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolLaura Gauthier is a senior computational biologist and director-level leader with 12 years of experience building scalable genomics, transcriptomics, and proteomics solutions that integrate AI/ML into biomedical research. She has led multidisciplinary teams of 25–30 engineers and scientists at the Broad Institute, delivering large-scale pipelines for cohorts of hundreds of thousands of samples, cost-saving cloud optimizations, and ML models for eQTL and somatic variant classification. Her technical work spans hands-on pipeline and tool development—including notable contributions to the widely used GATK project to make VariantRecalibrator more memory-efficient and flexible—and ownership of production WDL workflows. Now at Myriad Genetics, she combines strategic vision with operational rigor, aligning resources and stakeholder needs to bring research methods into clinical and product settings. Trained as a biomedical engineer with a PhD from Johns Hopkins, she blends deep computational expertise with experimental insight and a track record of translating method development into measurable savings and faster analyses. Colleagues describe her as an exceptional communicator who mentors teams to ship robust, reproducible genomics software.
12 years of coding experience
4 years of employment as a software developer
PhD, Biomedical/Medical Engineering, PhD, Biomedical/Medical Engineering at The Johns Hopkins University School of MedicineJohns Hopkins University
Github Skills (4)
java10
genomics10
javas10
bioinformatics10
Programming languages (10)
Github contributions (5)
broadinstitute/gatk
Jul 2017 - Jan 2023
Official code repository for GATK versions 4 and up
Role in this project:
Back-end Developer
Back-end DeveloperContributions:207 reviews, 189 commits, 190 PRs in 5 years 6 months
Contributions summary:Laura's contributions focused on enhancing the functionality of the VariantRecalibrator tool within the GATK project, specifically improving its memory efficiency and flexibility. They implemented features to handle pre-sampling data, output and read VQSR models, and enable the scattering of the VariantRecalibrator. The work included modifications to the core Java code, including the addition of new arguments, and refactoring code to support the new features. These changes improved the tool's ability to handle large datasets and provided more control over the recalibration process.
genomesciencednaspark-mlngs
broadinstitute/MuTest
Dec 2015 - Dec 2015
Contributions:5 commits, 4 PRs, 5 pushes in 1 day
storingsomatic-variantsprototypedatabasesomatic
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