Caitlin Guccione is a Senior Bioinformatics Scientist with nine years of experience applying applied mathematics, machine learning, and software engineering to oncology-focused microbiome research. Currently completing a PhD in Bioinformatics and Systems Biology at UC San Diego, she has developed and optimized production-ready pipelines for detecting microbes in tumor tissue and cell-free microbial DNA, and used differential abundance and random forest models to uncover disease-associated microbial signatures. Her background spans academic and industry roles—from implementing LIMS and cloud genomics workflows to creating purity-estimation tools for cancer samples—bridging reproducible engineering with biological insight. Based in San Diego, she combines rigorous modeling of microbial evolution in cancer with hands-on pipeline deployment at scale, making her adept at translating complex computational methods into actionable translational research.
8 years of coding experience
7 years of employment as a software developer
University of California, San Diego
Master's degree, Applied Mathematics, Master's degree, Applied Mathematics at University of Rhode Island
Pipeline which removes human DNA from microbial shotgun samples.
Contributions:8 PRs, 47 pushes, 4 branches in 1 year 6 months
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