Summary
David Gibbs is an applied ML scientist and senior research leader with 14 years of experience developing AI-driven solutions for computational biology and immuno-oncology. He leads cloud-scale engineering for the CRDC Imaging Data Commons, overseeing infrastructure for a 36TB+ cancer imaging repository used by international consortia. His work blends foundation-model development for digital pathology with integrative multi-omics analysis—combining single-cell and spatial transcriptomics, whole-slide imaging, and clinical data—to discover predictive biomarkers for immunotherapy. He builds scalable Google Cloud workflows (BigQuery, Docker) and authors open-source tools such as gssnng that integrate into the Scanpy ecosystem. A seasoned collaborator and mentor, he has co-led multi-institutional projects, contributed to grant writing for multi-million dollar initiatives, and published extensively (39 papers, h-index 19). Based in Seattle, he brings a rare combination of hands-on ML model engineering, cloud-native bioinformatics, and translational impact across pathology and clinical teams.
14 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy (PhD), Bioinformatics and Computational Biology, Doctor of Philosophy (PhD), Bioinformatics and Computational Biology at OHSU
B.A, Chemistry; Inorganic Chemistry, B.A, Chemistry; Inorganic Chemistry at Reed College
Postbac, Computer Science, Postbac, Computer Science at Portland State University, Portland Oregon
English