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multilevel methods

Amin Wu

Amin Wu successfully defended her PhD Thesis

1 min read · Tue, Mar 3 2026

News

bayesian inference stochastic processes stochastic differential equations multilevel methods

On March 3, 2026, Amin Wu successfully defended her PhD Thesis entitled "Bayesian Inference for Partially Observed Continuous-Time Processes".
StochNum and Math4UQ participants SNSL Workshop 2025

New CRG award to develop scalable methods for partially observed stochastic optimal control

1 min read · Sat, Feb 28 2026

News

award uncertainty quantification Stochastic Optimal Control multilevel methods Computational mathematics

KAUST Stochastic Numerics has been awarded a $900,000 Competitive Research Grant (CRG) for a 36‑month project on efficient hierarchical approximations for partially observed stochastic optimal control, co-led with Prof. Ibrahim Hoteit and including subawards to EPFL (Prof. Fabio Nobile) and WIAS Berlin (Prof. Christian Bayer).

Hamza M. Ruzayqat

Research Scientist, Omar Knio Research Group

monte carlo algorithms uncertainty quantification multilevel methods data assimilation Inverse problem bayesian inference MCMC

Dr. Hamza Ruzayqat is a Research Scientist at KAUST, specializing in Monte Carlo algorithms, data assimilation, and uncertainty quantification, with a background that includes a PhD in Mathematics from the University of Tennessee-Knoxville and various teaching and research positions.

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