Ph.D. Numerical Analysis, Royal Institute of Technology, 2002
M.S. Engineering Mathematics, Universidad de la Republica, Montevideo, Uruguay, 1999
B.S. Industrial and Mechanical Engineering, Universidad de la Republica, Montevideo, Uruguay, 1995
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.
Hoel, H., Shaimerdenova, G., & Tempone, R. (2022). Multi-index ensemble Kalman filtering. Journal of Computational Physics, 111561.
Cramer, E., Mitsos, A., Tempone, R., & Dahmen, M. (2022). Principal component density estimation for scenario generation using normalizing flows. Data-Centric Engineering, 3.
Kiessling, J., Ström, E., & Tempone, R. (2021). Wind field reconstruction with adaptive random Fourier features. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 477(2255). doi:10.1098/rspa.2021.0236
Espath, L., Kabanov, D., Kiessling, J., & Tempone, R. (2021). Statistical learning for fluid flows: Sparse Fourier divergence-free approximations. Physics of Fluids, 33(9), 097108. doi:10.1063/5.0064862
Nadhir Ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone , On the Efficient Simulation of Outage Probability in a Log-normal Fading Environment,IEEE Transactions on Communications 65 Issue: 6, 2017
F. Ruggeri, Z. Sawlan, M. Scavino, R. Tempone, A hierarchical Bayesian setting for an inverse problem in linear parabolic PDEs with noisy boundary conditions, Bayesian Analysis, Advance Publication, 12 May 2016. doi: 10.1214/16-BA1007
C. Bayer, J Happola, R. Tempone, Implied Stopping Rules for American Basket Options from Markovian Projection, arXiv:1705.00558v1, May 2017
A. Haji-Ali, R. Tempone, "Multilevel and Multi-index Monte Carlo methods for the McKean-Vlasov equation", has been accepted for publication in Statistics and Computing. 20
M. Iglesias, Z. Sawlan, M. Scavino, R. Tempone, C. Wood, Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements, accepted for publication in International Journal of Heat and Mass Transfer, Sep. 2017