geostatistics

SPDE-Based Geostatistical and Point Process Models for Environmental and Urban Network Applications

Damilya Saduakhas, Ph.D. Student, Statistics

Apr 15, 13:00 - 15:00

B5 R5209; Zoom Meeting 96585312249

SPDEs geostatistics oceanography monitoring multivariate spatial processes environmental applications

This thesis develops statistical models based on stochastic partial differential equations (SPDEs) for geostatistical and point process data, with applications to oceanographic monitoring, traffic safety, and urban air quality.

rSPDE

Research Resources

spatial statistics applied statistics Gaussian random fields SPDEs bayesian inference geostatistics

rSPDE: A Computational Framework for Rational Approximations of Fractional Stochastic Partial Differential Equations

Raphaël Huser

Associate Professor, Statistics

Statistics of extremes extreme-value theory spatio-temporal statistics data science machine learning copulas Environmental Statistics geostatistics applications to finance applications to neuroscience

Professor Huser develops novel statistical methodology and machine learning solutions to model and predict extreme events in various applications ranging from climate and earth sciences to finance and neuroscience.