Unit

Chair of Computational Mathematics and Simulation Science

Laboratory

Summary

The Computer Mathematics and Simulation Science (MCSS) laboratory at EPFL, under the direction of Professor Jan S. Hesthaven, focuses on developing high-order accurate computational methods for time-dependent partial differential equations. Research areas include discontinuous Galerkin and spectral methods, certified reduced basis methods, uncertainty quantification, multiscale problems, fractional differential equations, and machine learning techniques. The lab emphasizes tying theoretical developments to real applications in electromagnetics, plasma physics, combustion, and geoscience. Additionally, there is a strong interest in parallel computing, GPU acceleration, and resilient algorithms for large-scale predictive simulation science.

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Summary

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Related people (1)

Jan Sickmann Hesthaven

Prof. Hesthaven received an M.Sc. in computational physics from the Technical University of Denmark (DTU) in August 1991. During the studies, the last 6 months of 1989 was spend at JET, the european fusion laboratory in Culham, UK. Following graduation, he was awarded a 3 year fellowship to begin work towards a Ph.D. at Riso National Laboratory in the Department of Optics and Fluid Dynamics. During the 3 years of study, the academic year of 1993-1994 was spend in the Division of Applied Mathematics at Brown University and three 3 months during the summer of 1994 in Department of Mathematics and Statistics at University of New Mexico. In August 1995, he recieved a Ph.D. in Numerical Analysis from the Institute of Mathematical Modelling (DTU). Following graduation in August 1995, he was awarded an NSF Postdoctoral Fellowship in Advanced Scientific Computing and was approinted Visiting Assistant Professor in the Division of Applied Mathematics at Brown University. In December of 1996, he was appointed consultant to the Institute of Computer Applications in Science and Engineering(ICASE) at NASA Langley Research Center (NASA LaRC). As of July 1999, he was appointed Assistant Professor of Applied Mathematics, in September 2000 he was awarded an Alfred P. Sloan Fellowship, as of July 2001 he was awarded a Manning Assistant Professorship, and in March 2002, he was awarded an NSF Career Award. In January 2003, he was promoted to Associate Professor of Applied Mathematics with tenure and in May 2004 he was awarded Philip J. Bray Award for Excellence in Teaching in the Sciences (the highest award given for teaching excellence in all sciences at Brown University). He was promoted to Professor of Applied Mathematics as of July 2005. From October 2006 to June 2013, he was the Founding Director of the Center for Computation and Visualization (CCV) at Brown University. As of October 2007, he holds the (honorary) title of Professor (Adjunct) at the Technical University of Denmark. In November 2009, he successfully defended his dr.techn thesis at the Technical University of Denmark and was rewarded the degree of Doctor Technices -- the highest academic distinction awarded based on ... substantial and lasting contributions that has helped to move the research area forward and penetrated into applications. As grant Co-PI he served from Aug 2010 to June 2013 as Deputy Director of the Institute of Computational and Experimental Research in Mathematics (ICERM), the newest NSF Mathematical Sciences Research Institute. After having spend his entire academic career at Brown University, Prof Hesthaven decided to pursue new challenges and joined the Mathematics Institute of Computational Science and Engineering (MATHICSE) at Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland in July 2013. In March 2014 he was elected SIAM Fellow for contributions to high-order methods for partial differential equations.

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Related publications (30)

Related people (1)

Jan Sickmann Hesthaven

Chair of Computational Mathematics and Simulation Science

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Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

SPACE-TIME REDUCED BASIS METHODS FOR PARAMETRIZED UNSTEADY STOKES EQUATIONS

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE