SPDEs

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

Statistical Models and Methods Based on Stochastic Partial Differential Equations

David Bolin, Professor, Statistics

Mar 23, 14:00 - 15:30

B9 L2 R2322; Zoom Meeting ID 93209452060

SPDEs non-Gaussian random fields statistical analysis Metric graphs

This talk presents an overview of our research on statistical methods using stochastic partial differential equations (SPDEs), focusing on non-Gaussian random fields and fractional-order SPDEs, and theory for random fields and statistical analysis on metric graphs, highlighting theoretical contributions, software development, and applications relevant to KAUST RDI pillars.