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David earned an Associates of Arts degree when he was seventeen years old. In four years at the University of Washington, he earned two Bachelor of Science degrees in Biochemistry and Computer Science. In pursuit of his interest in applying Machine Learning and Artificial Intelligence to advance human health and wellness, David joined ISB at its inception in 2000. David earned a Master of Science degree in Computer Science from Washington University in St. Louis. In graduate school, his research centered on Computational Genomics focused on Gene Prediction. In 2004, David began working on Computational Proteomics at ISB. He has contributed computational tools, articles and lectures that continue to advance the field of mass spectrometry-based proteomics and analysis. David has been continuously developing analytical, computational and interactive visualization software tools for the Trans-Proteomics Pipeline (TPP) since its beginning. Some of his primary software contributions to the field of Proteomics include: iProphet for statistical validation of spectrum assignments, reSpect for identification of chimeric spectra, PTMProphet for statistical analysis of peptides containing post-translational modifications, ProteoGrapher for interactive visualization of protein lists in the context Gene Ontologies, and DISCO for Data Independent Acquisition (DIA) data analysis, among many others. David lives in Seattle with his wife, four children and ginger tom.

M.S., Computer Science, Washington University in St. Louis, 2004

B.S., Computer Science, University of Washington, 2001

B.S., Biochemistry, University of Washington, 2001

Machine Learning, Bayesian Inference, Artificial Intelligence, Signal Processing, Computational Proteomics, Mass Spectrometry