Evidence & Insights
A Statistical Approach for Identifying Private Wells Susceptible to Perfluoroalkyl Substances (PFAS) Contamination
Monitoring PFAS contamination can be costly and time consuming. We developed and evaluated a machine learning model to identify private wells susceptible to PFAS contamination.Learn more
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Research and Evaluation
Program Design and Improvement
COVID-19 Scalable Services
Vice President; Director of Health Program ImprovementView Bio Page
Senior ResearcherView Bio Page
Principal ResearcherView Bio Page