Katie Saund is a computational biologist with a decade of experience applying statistical and machine learning approaches to RNA-seq, single-nucleus RNA-seq, metabolomics, and genomics for biomarker discovery and neurodegeneration research. Currently a Scientist at Denali Therapeutics, she integrates multiomic datasets and develops workflows for differential expression, splicing, GSEA, and predictive modeling while managing access to diverse public cohorts. Her research foundation includes a PhD in Microbiology & Immunology from the University of Michigan and tool development for bacterial GWAS (including the CRAN package prewas and the hogwash package). She has bridged academia, industry, and translational projects—from infectious disease genomics to cancer immunology—and has experience evaluating biotech investments through student-led venture work. On a career break and based in the San Francisco Bay Area, she remains open to collaborations and discussions around biomarker-driven biotech problems and reproducible computational tooling.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Microbiology and Immunology, Doctor of Philosophy (Ph.D.), Microbiology and Immunology at University of Michigan
Bachelor of Science (B.Sc.), Biology, Bachelor of Science (B.Sc.), Biology at California Institute of Technology
Contributions:3 releases, 231 pushes, 5 branches in 1 year 3 months
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