Jan S. Hesthaven
Domaines de compétences
While the emphasis in on the development and analysis of new methods and algorithms, the research is application driven and we generally maintain a strong focus on tying the theoretical developments to real applications, ranging from electromagnetics and plasma physics to geoscience and combustion. There is also a sustained interest in the development of methods and algorithms for parallel computing, GPU accelerated computing and the development of resilient algorithms, to support the development and use of large scale computational tool to enable predictive similation science.
BiographieProf. 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.
Master of Science
Technical University of Denmark
Doctor of Philosophy (PhD)
Technical University of Denmark
Doctor Technices (dr.techn)
Technical University of Denmark
NSF Postdoctoral Fellowship
US National Science Foundation
Alfred P. Sloan Research Fellowship
Alfred P Sloan Foundation, US
Manning Assistant Professorship
Brown University, US
NSF Career Award
US National Science Foundation
Gutenberg Foundation, France
Elected SIAM Fellow
Society of Industrial and Applied Mathematics, US
Jan S Hesthaven publications
Rank-adaptive structure-preserving model order reduction of Hamiltonian systemsEsaim-Mathematical Modelling And Numerical Analysis. 2022-03-08. DOI : 10.1051/m2an/2022013.
Multi-fidelity regression using artificial neural networks: Efficient approximation of parameter-dependent output quantitiesComputer Methods In Applied Mechanics And Engineering. 2022-02-01. DOI : 10.1016/j.cma.2021.114378.
Preface to Focused Issue on Discontinuous Galerkin Methods PREFACECommunications On Applied Mathematics And Computation. 2021-10-08. DOI : 10.1007/s42967-021-00170-1.
Structure-Preserving Reduced Basis Methods For Poisson SystemsMathematics Of Computation. 2021-07-01. DOI : 10.1090/mcom/3618.
Non-Intrusive Reduced Order Modeling of Convection Dominated Flows Using Artificial Neural Networks with Application to Rayleigh-Taylor InstabilityCommunications In Computational Physics. 2021-07-01. DOI : 10.4208/cicp.OA-2020-0064.
Modeling synchronization in globally coupled oscillatory systems using model order reductionChaos. 2021-05-01. DOI : 10.1063/5.0031142.
Discovery of slow variables in a class of multiscale stochastic systems via neural networksArXiv. 2021-04-28.
A phenomenological extended-reaction boundary model for time-domain wave-based acoustic simulations under sparse reflection conditions using a wave splitting methodApplied Acoustics. 2021-01-15. DOI : 10.1016/j.apacoust.2020.107596.
A Local Discontinuous Galerkin Method for Two-Dimensional Time Fractional Diffusion EquationsCommunications On Applied Mathematics And Computation. 2020-12-01. DOI : 10.1007/s42967-020-00065-7.
Characterization of image spaces of Riemann-Liouville fractional integral operators on Sobolev spaces W-m,W-p (omega)Science China-Mathematics. 2020-11-18. DOI : 10.1007/s11425-019-1720-1.
Time-domain room acoustic simulations with extended-reacting porous absorbers using the discontinuous Galerkin methodJournal Of The Acoustical Society Of America. 2020-11-01. DOI : 10.1121/10.0002448.
Controlling oscillations in spectral schemes using Artificial Neural Networks2020-09-14
Massive parallel nodal discontinuous Galerkin finite element method simulator for room acousticsInternational Journal of High Performance Computing Applications. 2020-09-06.
Apparent diffusion coefficient measured by diffusion MRI of moving and deforming domainsJournal Of Magnetic Resonance. 2020-09-01. DOI : 10.1016/j.jmr.2020.106809.
Physics-informed machine learning for reduced-order modeling of nonlinear problems2020-07-23.
Rare event simulation for large-scale structures with local nonlinearitiesComputer Methods In Applied Mechanics And Engineering. 2020-07-01. DOI : 10.1016/j.cma.2020.113051.
A non-intrusive multifidelity method for the reduced order modeling of nonlinear problemsComputer Methods In Applied Mechanics And Engineering. 2020-06-01. DOI : 10.1016/j.cma.2020.112947.
Constraint-aware neural networks for Riemann problemsJournal Of Computational Physics. 2020-05-15. DOI : 10.1016/j.jcp.2020.109345.
Controlling oscillations in high-order Discontinuous Galerkin schemes using artificial viscosity tuned by neural networksJournal Of Computational Physics. 2020-05-15. DOI : 10.1016/j.jcp.2020.109304.
Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health MonitoringComputer Methods In Applied Mechanics And Engineering. 2020-05-01. DOI : 10.1016/j.cma.2020.112896.
A Study of Several Artificial Viscosity Models within the Discontinuous Galerkin FrameworkCommunications In Computational Physics. 2020-05-01. DOI : 10.4208/cicp.OA-2019-0118.
A Homotopy Method with Adaptive Basis Selection for Computing Multiple Solutions of Differential EquationsJournal Of Scientific Computing. 2020-01-13. DOI : 10.1007/s10915-020-01123-1.
Effective diffusion tensor measured by diffusion MRI of moving and deforming domainsJournal of Magnetic Resonance. 2020.
Modeling extended-reaction boundary conditions in time-domain wave-based simulations of room acoustics2019-10-31.
Time domain room acoustic simulations using the spectral element methodJournal Of The Acoustical Society Of America. 2019-06-01. DOI : 10.1121/1.5109396.
Structure-Preserving Model-Reduction of Dissipative Hamiltonian SystemsJournal of Scientific Computing. 2019. DOI : 10.1007/s10915-018-0653-6.
RBF Based CWENO Method2018-11-09. ICOSAHOM 2018, London, UK.
Conservative Model Order Reduction for Fluid FlowAdvances in reduced order modeling; Springer Verlag, 2018-08-06.
A data-driven shock capturing approach for discontinuous Galekin methods2018-06-18.
Controlling oscillations in high-order schemes using neural networks2018
Structure-Preserving Reduced Basis Methods for Hamiltonian Systems with a State-dependent Poisson StructureMathematics of computation. 2018.
Symplectic Model-Reduction with a Weighted Inner ProductSIAM Journal of Scientific Computing. 2018.
Numerical methods for conservation laws: From analysis to algorithmsPhiladelphia: SIAM Publishing.
A comparative study of shock capturing models for the discontinuous Galerkin methodJournal of Computational Physics. 2017.
Large-Scale Tsunami Simulations using the Discontinuous Galerkin Method27th Biennial Conference on Numerical Analysis, Glasgow, UK, June 27-30, 2017.
A greedy non-intrusive reduced order model for fluid dynamicsJournal of Northwestern Polytechnical University. 2017.
Spectral methods for tempered fractional differential equationsMathematics of Computation. 2016.
Efficient Absorbing Layers for Weakly Compressible Flows2016
Enseignement & Phd
Doctoral Program in Mathematics
Doctoral Program in Physics