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 spatiotemporal optimization engine for prescribed burning in the Southeast US , ECOLOGICAL INFORMATICS (2024)
• Bayesian inference informed by parameter subset selection for a minimal PBPK brain model , PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2025)
• Bivariate DeepKriging for Large-Scale Spatial Interpolation of Wind Fields , TECHNOMETRICS (2025)
• Distributed model building and recursive integration for big spatial data modeling , BIOMETRICS (2025)
• 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)
• Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras , CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES (2024)
• DEEPKRIGING: SPATIALLY DEPENDENT DEEP NEURAL NETWORKS FOR SPATIAL PREDICTION , STATISTICA SINICA (2022)
• 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)