SUMMARY
Public-health geneticist and molecular epidemiologist with 17 years designing and executing a wide range of epidemiological studies in humans. Experience in biotech, government, academia, and consulting offering R&D guidance for a biotech and surveillance for the State of Washington. Multidisciplinary training applied at three cancer-research centers: National Cancer Institute, the Fred Hutch, and City of Hope. Tech savvy: proficiency in R and bash and advanced causal inference and statistical genetics methods. Bioinformatics tools and Python employed on an ad-hoc basis. Teaching experience in genomics, writing, and rhetoric at three universities. Committed mentor to more-junior scientists and enthusiastic science communicator and writer. Particular expertise in integrative, molecular approaches for mechanistic insights that can provide evidence for or against clinical trials. Comfortable harnessing new biological technologies, such as the latest omics. Visionary with powerful ideas for identifying those susceptible to disease years in advance and for predicting biomarkers of treatment response (vs prognosis) in patients. Lifelong dedication to saving and improving lives.
HIGHLIGHTS
17 years designing & conducting etiological, biomarker, & real-world data (RWD) studies in humans, including integrative omics for drug-target identification & drug repurposing.
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Biomedical Research: 3 cancer-research centers, 3 governmental agencies, & 4 universities.
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Teaching Experience: 3 universities.
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Data Science & Translational Research: Applied statistical genetics & molecular epidemiology.
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Machine Learning: Prediction & novel biomarker discovery.
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Main Epidemiological Content Areas: cancer, aging, metabolic, neuroscience, chronic disease, reproductive, & integrative.
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Coding Skills: R, command line, & high-performance computing (HPC).
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Consulting: State of Washington's Newborn Screening Program & a biotech start-up, providing R&D guidance.
