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Omar Knio

Professor, Applied Mathematics and Computational Science

Vice President, Education and Academic Affairs

Principal Investigator, Omar Knio Research Group

Computer, Electrical and Mathematical Science and Engineering Division
Email icon omar.knio@kaust.edu.sa

When in doubt, compute!

Program Affiliations

Biography

Omar Knio received his Ph.D. in mechanical engineering in 1990 from the Massachusetts Institute of Technology (MIT) in the United States. He held a postdoctoral associate position at MIT before joining the mechanical engineering faculty at Johns Hopkins University in 1991. In 2011, he joined the Department of Mechanical Engineering and Materials Science at Duke University, where he also served as associate director of the Center for Material Genomics. In 2012, he was named the Edmund T. Pratt, Jr. Professor of Mechanical Engineering and Materials Science at Duke.

In 2013, Knio joined the Applied Mathematics and Computational Sciences (AMCS) Program at KAUST, where he also served as deputy director of the SRI Center for Uncertainty Quantification in Computational Science and Engineering and as the interim dean of the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. In 2024, he was appointed associate vice president of National Partnerships, Engagement and Academic Liaison, at the KAUST National Transformation Institute.

He is a founding associate editor of the SIAM/ASA Journal on Uncertainty Quantification and currently serves on the editorial boards of the International Journal for Uncertainty Quantification and Theoretical and Computational Fluid Dynamics.

Knio has received several awards, including the Associated Western Universities Faculty Fellowship Award in 1996, the Friedrich Wilhelm Bessel Award in 2003, the R&D 100 Award in 2005, the Distinguished Alumnus Award from the American University of Beirut in 2005, and the Abdul-Hameed Shoman Award for Arab Researchers in 2019.

Research Interests

Professor Knio’s research interests include uncertainty quantification, Bayesian inference, combustion, oceanic and atmospheric flows, physical acoustics, energetic materials, microfluidic devices, renewable energy systems, high-performance computing, optimization under uncertainty, and data-enabled predictive science.
Keyword tag icon
uncertainty quantification bayesian inference computational fluids mechanics combustion High Performance Computing

Education Profile

  • Doctor of Philosophy (Ph.D) Mechanical Engineering, Massachusetts Institute of Technology, United States, 1990

  • Master of Science (M.S) Mechanical Engineering, Massachusetts Institute of Technology, United States, 1986

  • Bachelor of Engineering (B.Eng.) Mechanical Engineering, American University of Beirut, Lebanon, 1984

Awards and Recognitions

  • R&D 100 Award, 2005

  • Distinguished Alumnus Award, American University of Beirut, 2005

  • Friedrich Wilhelm Bessel Award, Humboldt Foundation, 2003

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.

Research Areas

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