bayesian inference

Omar Knio Research Group

bayesian inference computational fluids mechanics uncertainty quantification

Professor Omar Knio leads the so-called O-Knio research group, which stands for Omar Knio Research Group Research group areas of expertise and current scientific interests: bayesian inference, computational fluids mechanics, uncertainty quatification ‌Led by Prof. Omar Knio, the O-Knio research group. His research interests include uncertainty quantification, Bayesian inference, computational fluid mechanics, combustion, oceanic and atmospheric flows, turbulent flow, physical acoustics, energetic materials, microfluidic devices, dynamical systems, asymptotic techniques, multi-resolution

Omar Knio

Professor, Applied Mathematics and Computational Sciences

uncertainty quantification bayesian inference computational fluids mechanics combustion High Performance Computing

Professor Knio focuses on developing state-of-the-art methods and algorithms for simulating complex multiscale systems, and their implementation to the analysis and optimization of renewable energy systems.

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.