User:Rtempone

Biography
Raul Tempone is a distinguished professor known for his contributions to numerical analysis, stochastic numerics, and uncertainty quantification. He has served in prominent positions across various institutions including KAUST, RWTH Aachen, and the KTH Royal Institute of Technology. His research interests span a wide range, focusing on the development of numerical methods to address complex problems in engineering and applied sciences.

Education

 * PhD in Numerical Analysis - Royal Institute of Technology (KTH), Sweden. Thesis: "Numerical Complexity Analysis of Weak Approximation of Stochastic Differential Equations".
 * Licenciate Teknolog - Royal Institute of Technology (KTH), Sweden.
 * Magister in Mathematical Engineering - Universidad de la República, Uruguay.
 * Industrial Engineer - Universidad de la República, Uruguay.

Awards and Honors

 * Keynote speaker, at various international conferences (2016-2024).
 * Alexander von Humboldt Professorship, hosted by RWTH Aachen, Germany (2018-2025).
 * Thomson Reuters Highly Cited Researcher (2016).
 * First awardee of the "Dahlquist Research Fellowship" at the Royal Institute of Technology, Sweden (2007-2008).

Professional Memberships

 * American Mathematical Society (AMS)
 * International Association of Computational Mechanics (IACM)
 * Society for Industrial and Applied Mathematics (SIAM)
 * United States Association for Computational Mechanics (USACM)
 * Association of Applied Mathematics and Mechanics (GAMM)
 * Centre International de Mathématiques Pures et Appliquées (CIMPA)

Research Interests

 * Numerical Analysis
 * Stochastic Numerics
 * Stochastic Differential Equations
 * Uncertainty Quantification
 * Verification and Validation
 * Adaptive Algorithms
 * Stochastic Optimal Control
 * Bayesian Inverse Problems

Supervision of Students
Professor Tempone has supervised a significant number of PhD, MSc, and undergraduate students, contributing to the development of future researchers in the field. His supervision spans across institutions such as KAUST and KTH Stockholm, covering a wide range of topics from stochastic differential equations to computational finance.