computational methods

KAUST-CEMSE-STAT-STSDS-Sihan-Chen

On Computation and Robustness Issues in Spatial Statistics

Sihan Chen, Ph.D. Student, Statistics

Oct 30, 14:30 - 16:30

B2, L5, R5220

robust spatial inference computational methods spatial statistics

This thesis develops and evaluates robust statistical methods for the analysis and modeling of spatial data, with a focus on improving inference reliability in the presence of outliers and computational challenges.

Peter Schmid

Professor, Mechanical Engineering

applied mathematics computational methods Signal processing MATLAB

Professor Schmid's research interests are in theoretical and computational fluid dynamics, with emphasis on hydrodynamic stability theory, flow control, model reduction and system identification. He is also interested in computational techniques for flow optimization and quantitative flow analysis.