Brian Reich

Bio

Brian uses geospatial analytics to explore patterns in data from the environmental, physical and materials sciences. He develops approaches using spatial statistics, extreme value analysis, quantile regression, variable selection and dimension reduction. His interests include both methodological questions in statistics and applications of statistical methods to problems such as air pollution and climate change.

Publications

• A Gaussian-process approximation to a spatial SIR process using moment closures and emulators , BIOMETRICS (2024)
• A diverse portfolio of marine protected areas can better advance global conservation and equity , PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2024)
• Estimating spatially varying health effects of wildland fire smoke using mobile health data , JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS (2024)
• MODELING EXTREMAL STREAMFLOW USING DEEP LEARNING APPROXIMATIONS AND A FLEXIBLE SPATIAL PROCESS , ANNALS OF APPLIED STATISTICS (2024)
• Measurement of Hydro-EVE and 6:2 FTS in Blood from Wilmington, North Carolina, Residents, 2017-2018 , ENVIRONMENTAL HEALTH PERSPECTIVES (2024)
• Modeling wildland fire burn severity in California using a spatial Super Learner approach , ENVIRONMENTAL AND ECOLOGICAL STATISTICS (2024)
• Reanalysis of PFO5DoA Levels in Blood from Wilmington, North Carolina, Residents, 2017-2018 , ENVIRONMENTAL HEALTH PERSPECTIVES (2024)
• Regime-based precipitation modeling: A spatio-temporal approach , SPATIAL STATISTICS (2024)
• The R2D2 Prior for Generalized Linear Mixed Models , AMERICAN STATISTICIAN (2024)
• A Data-Fusion Approach to Assessing the Contribution of Wildland Fire Smoke to Fine Particulate Matter in California , REMOTE SENSING (2023)