Profiles

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.

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.

In 2019, Dr. Ruzayqat received his PhD in Mathematics from the University of Tennessee-Knoxville, USA. In 2012, he received a Bachelor degree in Physics and mathematics from Birzeit University, Palestine. Dr. Hamza Ruzayqat joined KAUST in November 2019 as a Post-Doctoral Research Fellow in the group of Computational Probability (COMPPROB). Late in 2022, he was promoted to Research Scientist and now a member in Omar Knio's Research Group. 

Dr. Ruzayqat main research is focused on Monte Carlo algorithms, data assimilation and uncertainty quantification. In particular, he is working on particle filters, SMCMC filters, unbiased estimators, inverse problems, parameter estimation and Bayesian inference in discrete/continuous-time, linear/nonlinear, low or high dimensional state-space models. In the past he worked on off-lattice kinetic Monte Carlo methods for atomic simulations.

Ricardo has a Chemical Engineering Diploma (5 years degree) and a PhD in Chemical Engineering in the area of Process Systems Engineering. He obtained his Diploma and PhD at the Faculty of Engineering from the University of Porto (FEUP), Portugal, under the supervision of Professor Romualdo Salcedo and Professor Domingos Barbosa.

After completing his PhD studies, Ricardo became a post-doctoral fellow in the Department of Chemical Engineering at the Carnegie Mellon University (CMU), USA, where he worked with Professor Ignacio Grossmann. During his stay at CMU, he collaborated with PPG Industries in several projects. He was an invited researcher in the Glass Process Engineering/Process Control group located in the PPG Glass Business and Discovery Center, where he worked with Dr Yu Jiao.

In 2011, Ricardo was awarded a Marie Curie Fellowship to pursue research on sustainable power systems at the National Laboratory of Energy and Geology in Portugal.

Ricardo joined KAUST in 2014, where he has been involved in problems concerning chemical processes flexibility, optimization of isolated and hybrid energy systems, the motion planning of autonomous underwater vehicles, optimal operation of virtual power plants, optimization under uncertainty, robust optimization, and in a project with the Ministry of Health of Saudi Arabia.

My research interests lie at the intersection of optimization, modeling, uncertainty, and computer science. I am interested in the modeling and optimization of complex problems related to energy systems, chemical engineering, and oil industries. Target applications include integration, planning and scheduling of renewable energy systems, process synthesis, planning and scheduling of chemical engineering systems, and path planning of autonomous under-water vehicles. Development of mathematical programming methodologies, namely combinatorial optimization models, continuous optimization models, deterministic global optimization solution approaches, optimization under uncertainty models, and decomposition algorithms to solve large-scale problems.