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Omar Knio

Professor, Applied Mathematics and Computational Science

Computer, Electrical and Mathematical Science and Engineering Division

omar.knio@kaust.edu.sa


Affiliations

Education Profile

  • Ph.D. Mechanical Engineering, Massachusetts Institute of Technology, USA, 1990
  • S.M. Mechanical Engineering, Massachusetts Institute of Technology, USA, 1986
  • B.E. in Mechanical Engineering, American University of Beirut, Lebanon, 1984

Research Interests

​Professor Knio’s 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 methods, high-performance computing, optimization under uncertainty, and data-enabled predictive science.

Selected Publications

  • F. Rizzi, R. Jones, B.J. Debusschere, O.M. Knio “Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. Part II: uncertain potential parameters.” J. Chem. Phys. 138, 194105, 2013.
  • I. Sraj, M. Iskandarani, A. Srinivasan, W.C. Thacker, J. Winokur, A. Alexanderian, C.-Y. Lee, S.S. Chen, O.M. Knio “Bayesian Inference of Dependence of Drag Coefficient on Wind Speed using AXBT data from Typhoon Fanapi.” Mon. Wea. Rev. 141, 2347-2367, 2013.
  • L. Alawieh, T.P. Weihs, O.M. Knio “A Generalized Reduced Model of Uniform and Self- Propagating Reactions in Reactive Nanolaminates.” Combust. Flame 160, 1857-1869, 2013.
  • A. Alexanderian, J. Winokur, I. Sraj, A. Srinivasan, M. Iskandarani, W.C. Thacker, O.M. Knio “Global Sensitivity Analysis in Ocean Global Circulation Models: A Sparse Spectral Projection Approach,” Comput. Geosci. 16, 757-778, 2012.
  • O.P. Le Maître, O.M. Knio, Spectral Methods for Uncertainty Quantification – With Applications to Computational Fluid Dynamics , Springer, 2010.