Raul F. Tempone
Department of Applied Mathematics and Computational Science
King Abdullah University of Science and Technology
Raul Tempone's research interests are in the mathematical foundation of computational science and engineering. More specifically, he has focused on a posteriori error approximation and related adaptive algorithms for numerical solutions of various differential equations, including ordinary differential equations, partial differential equations, and stochastic differential equations.
He is also interested in the development and analysis of efficient numerical methods for optimal control, uncertainty quantification and bayesian model calibration, validation and optimal experimental design. The areas of application he considers include, among others, engineering, chemistry, biology, physics as well as social science and computational finance.
Ruggeri F, Sawlan Z, Scavino M, Tempone R. A hierarchical Bayesian setting for an inverse problem in linear parabolic PDEs with noisy boundary conditions. Bayesian Analysis. 2017;12(2):407-33.
Rached NB, Kammoun A, Alouini MS, Tempone R. On the Efficient Simulation of Outage Probability in a Log-normal Fading Environment. IEEE Transactions on Communications. 2017 Feb 15.