Jan S. Hesthaven
EPFL SB-DO
PH A2 364 (Bâtiment PH)
Station 3
CH-1015 Lausanne
+41 21 69 33302
Site web: https://www.epfl.ch/schools/sb/about/deans-office/
Unité: SB-DO
Local: PH A2 364
Site web: https://www.epfl.ch/schools/sb/about/deans-office/
Unité: SB-DO
Local: PH A2 364
EPFL SB MATH MCSS
MA C2 652 (Bâtiment MA)
Station 8
CH-1015 Lausanne
Unité: SCITAS-CD
Publications
Jan S Hesthaven publications
2019
M. Sadr; M. H. Gorji : Treatment of long-range interactions arising in the Enskog-Vlasov description of dense fluids; Journal of Computational Physics. 2019-02-01. DOI : 10.1016/j.jcp.2018.11.005.
N. Discacciati; J. S. Hesthaven; D. Ray : Controlling oscillations in high-order Discontinuous Galerkin schemes using artificial\ viscosity tuned by neural networks. 2019-01-28.
P. Jenny; M. Gorji : Accurate particle time integration for solving Vlasov-Fokker-Planck equations with specified electromagnetic fields; Journal of Computational Physics. 2019. DOI : 10.1016/j.jcp.2019.02.040.
2018
J. S. Hesthaven; F. Mönkeberg; S. Zaninelli : RBF Based CWENO Method. 2018-11-09. ICOSAHOM 2018, London, UK.
Z. Zhang; M. Guo; J. S. Hesthaven : Model order reduction for large-scale structures with local nonlinearities. 2018-11-09.
D. Ray; J. S. Hesthaven : Detecting troubled-cells on two-dimensional unstructured grids using a neural network. 2018-11-01.
P. Cazeaux; J. S. Hesthaven : Projective multiscale time-integration for electrostatic particle-in-cell methods; Computer Physics Communications. 2018-10-19. DOI : 10.1016/j.cpc.2018.10.012.
M. Guo; J. S. Hesthaven : Data-driven reduced order modeling for time-dependent problems; Computer Methods in Applied Mechanics and Engineering. 2018-10. DOI : 10.1016/j.cma.2018.10.029.
J. S. Hesthaven; F. Mönkeberg : Entropy stable essentially non-oscillatory methods based on RBF reconstructions; Mathematical Modeling and Numerical Analysis. 2018-08-14.
M. Hajihassanpour; B. Bonev; J. S. Hesthaven : Validation study of static and dynamic tsunami source models using the discontinuous Galerkin method for the spherical shallow water equations. 2018-08-11.
B. Maboudi Afkham; N. Ripamonti; Q. Wang; J. S. Hesthaven : Conservative Model Order Reduction for Fluid Flow; Advances in reduced order modeling; Springer Verlag, 2018-08-06.
W. Chen; J. S. Hesthaven; B. Junqiang; Y. Qiu; Y. Tihao et al. : Greedy Non-Intrusive Reduced Order Model for Fluid Dynamics; AIAA Journal. 2018-06-24. DOI : 10.2514/1.J056161.
T. Lahivaara; A. Pasanen; L. Karkkainen; J. M. Huttunen; J. S. Hesthaven et al. : Estimation of groundwater storage from seismic data using deep learning; Geophysics Research Letters. 2018-06-24.
J. Yu; J. S. Hesthaven; C. Yan : A data-driven shock capturing approach for discontinuous Galekin methods. 2018-06-18.
Q. Wang; J. S. Hesthaven; D. Ray : Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem; Journal of Computational Physics. 2018-06-18. DOI : 10.1016/j.jcp.2019.01.031.
W. Chen; B. Junqiang; J. S. Hesthaven; Q. Yasong; Q. Lei et al. : POD-Kriging reduced method’s application in Tandem Cylinders’ flow; Journal of Northwestern Polytechnical University. 2018-06-01.
N. Discacciati : Controlling oscillations in high-order schemes using neural networks ; 2018.
A. Nielsen; G. Brunner; J. Hesthaven : Communication-aware adaptive Parareal with application to a nonlinear hyperbolic system of partial differential equations; Journal of Computational Physics. 2018. DOI : 10.1016/j.jcp.2018.04.056.
M. Gorji : Treatment of long-range interactions arising in the Enskog-Vlasov description of dense fluids; Journal of Computational Physics. 2018.
A. S. Nielsen / J. S. Hesthaven (Dir.) : Scaling and Resilience in Numerical Algorithms for Exascale Computing. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8926.
B. Maboudi Afkham / J. S. Hesthaven (Dir.) : Geometric Model Order Reduction. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8923.
A. Susnjara / D. Kressner (Dir.) : Fast hierarchical solvers for symmetric eigenvalue problems. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8808.
J. S. Hesthaven; C. Pagliantini : Structure-Preserving Reduced Basis Methods for Hamiltonian Systems with a Nonlinear Poisson Structure; Foundations of Computational Mathematics. 2018.
K. Shukla; J. S. Hesthaven; J. M. Carcione; R. Ye; J. de la Puenta et al. : A nodal discontinuous Galerkin finite element method for the poroelastic wave equation; Computational Geoscience. 2018. DOI : 10.1007/s10596-019-9809-1.
M. H. Gorji : Logarithmic Gradient Transformation and Chaos Expansion of Ito Processes. 2018.
A. Karakus; N. Chalmers; J. S. Hesthaven; T. Warburton : Discontinuous Galerkin Discretizations of the Boltzmann Equations in 2D: semi-analytic time stepping and absorbing boundary layers. 2018.
N. Dal Santo / A. Quarteroni; A. Manzoni (Dir.) : Multi space reduced basis preconditioners for parametrized partial differential equations. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8553.
B. Maboudi Afkham; A. Bhatt; B. Haasdonk; J. S. Hesthaven : Symplectic Model-Reduction with a Weighted Inner Product; SIAM Journal of Scientific Computing. 2018.
J. Yu; J. S. Hesthaven : Flowfield Reconstruction Method Using Artificial Neural Network; AIAA Journal. 2018. DOI : 10.2514/1.J057108.
M. Guo; J. S. Hesthaven : Reduced order modeling for nonlinear structural analysis using Gaussian process regression; Computer Methods in Applied Mechanics and Engineering. 2018. DOI : 10.1016/j.cma.2018.07.017.
B. Bonev; J. S. Hesthaven; F. X. Giraldo; M. A. Kopera : Discontinuous Galerkin scheme for the spherical shallow water equations with applications to tsunami modeling and prediction; Journal of Computational Physics. 2018. DOI : 10.1016/j.jcp.2018.02.008.
D. Ray; J. S. Hesthaven : An artificial neural network as a troubled-cell indicator; Journal of computational physics. 2018. DOI : 10.1016/j.jcp.2018.04.029.
J. S. Hesthaven; S. Ubbiali : Non-intrusive reduced order modeling of nonlinear problems using neural networks; Journal of Computational Physics. 2018. DOI : 10.1016/j.jcp.2018.02.037.
T. Lahivaara; L. Karkkainen; J. M. Huttunen; J. S. Hesthaven : Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography; Journal of the Acoustical Society of America. 2018. DOI : 10.1121/1.5024341.
U. Ruede; K. Willcox; L. C. McInnes; H. De Sterck; G. Biros et al. : Research and Education in Computational Science and Engineering; Siam Review. 2018. DOI : 10.1137/16M1096840.
2017
J. S. Hesthaven : Numerical methods for conservation laws: From analysis to algorithms ; Philadelphia: SIAM Publishing.
J. Yu; J. S. Hesthaven : A comparative study of shock capturing models for the discontinuous Galerkin method; Journal of Computational Physics. 2017.
P. Gatto; J. S. Hesthaven : Efficient Preconditioning of hp-FEM Matrices by Hierarchical Low-Rank Approximations; Journal Of Scientific Computing. 2017. DOI : 10.1007/s10915-016-0347-x.
E. Musharbash / F. Nobile (Dir.) : Dynamical Low Rank approximation of PDEs with random parameters. Lausanne, EPFL, 2017. DOI : 10.5075/epfl-thesis-7813.
B. Bonev; F. Giraldo; J. S. Hesthaven : Large-Scale Tsunami Simulations using the Discontinuous Galerkin Method ; 27th Biennial Conference on Numerical Analysis, Glasgow, UK, June 27-30, 2017.
A. S. Nielsen; G. Brunner; J. S. Hesthaven : Communication-aware adaptive parareal with application to a nonlinear hyperbolic system of partial dierential equations; Journal of Computational Physics. 2017. DOI : 10.1016/j.jcp.2018.04.056.
B. Maboudi Afkham; J. S. Hesthaven : Structure-Preserving Model-Reduction of Dissipative Hamiltonian Systems; Journal of Scientific Computing. 2017.
W. Chen; J. S. Hesthaven; B. Junqiang; Z. Yang; Y. Tihao : A greedy non-intrusive reduced order model for fluid dynamics; Journal of Northwestern Polytechnical University. 2017.
D. Baffet; J. S. Hesthaven : High-Order Accurate Local Schemes for Fractional Differential Equations; Journal Of Scientific Computing. 2017. DOI : 10.1007/s10915-015-0089-1.
M. Dam; M. Brøns; J. J. Rasmussen; V. Naulin; J. S. Hesthaven : Identification of a Predator-Prey System from Simulation Data of a Convection Model; Physics of Plasmas. 2017. DOI : 10.1063/1.4977057.
P. Gatto; J. S. Hesthaven; R. Christiansen : Efficient preconditioning of hp-FEM matrices arising from time-varying problems: an application to topology optimization; Computer Methods in Applied Mechanics and Engineering. 2017. DOI : 10.1016/j.cma.2017.04.027.
C. Bigoni; J. S. Hesthaven : Adaptive WENO methods based on radial basis functions reconstruction; Journal of Scientific Computing. 2017. DOI : 10.1007/s10915-017-0383-1.
D. H. Baffet; J. S. Hesthaven : High-Order Accurate Adaptive Kernel Compression Time-Stepping Schemes for Fractional Differential Equations; Journal of Scientific Computing. 2017. DOI : 10.1007/s10915-017-0393-z.
B. Maboudi Afkham; J. S. Hesthaven : Structure preserving model reduction of parametric Hamiltonian systems; Siam Journal on Scientific Computing. 2017. DOI : 10.1137/17M1111991.
S. Yeganeh; R. Mokhtari; J. S. Hesthaven : Space-dependent source determination in a time-fractional diffusion equation using a local discontinuous Galerkin method; BIT Numerical Mathematics. 2017. DOI : 10.1007/s10543-017-0648-y.
D. H. Baffet; J. S. Hesthaven : A kernel compression scheme for fractional differential equations; Siam Journal on Numerical Analysis. 2017. DOI : 10.1137/15M1043960.
2016
D. S. Guignard / F. Nobile; M. Picasso (Dir.) : A posteriori error estimation for partial differential equations with random input data. Lausanne, EPFL, 2016. DOI : 10.5075/epfl-thesis-7260.
O. Budáč / A. Abdulle (Dir.) : Multiscale methods for Stokes flow in heterogeneous media. Lausanne, EPFL, 2016. DOI : 10.5075/epfl-thesis-7135.
J. S. Hesthaven : Spectral Methods for Hyperbolic Problems; Handbook of Numerical Methods for Hyperbolic Problems Basic and Fundamental Issues; Elsevier Publishing, 2016. p. 441-466.
P. Sirkovic / D. Kressner (Dir.) : Low-rank methods for parameter-dependent eigenvalue problems and matrix equations. Lausanne, EPFL, 2016. DOI : 10.5075/epfl-thesis-7137.
V. H. Laurmaa / M. Picasso (Dir.) : An octree-based adaptive semi-Lagrangian free surface flow solver. Lausanne, EPFL, 2016. DOI : 10.5075/epfl-thesis-7011.
D. Forti / A. Quarteroni; S. Deparis (Dir.) : Parallel Algorithms for the Solution of Large-Scale Fluid-Structure Interaction Problems in Hemodynamics. Lausanne, EPFL, 2016. DOI : 10.5075/epfl-thesis-6983.
L. Zhao; W. Deng; J. S. Hesthaven : Spectral methods for tempered fractional differential equations; Mathematics of Computation. 2016.
A. S. Nielsen; J. S. Hesthaven : Fault Tolerance in the Parareal Method. 2016. ACM Workshop on Fault-Tolerance for HPC at Extreme Scale (FTXS). p. 1-8. DOI : 10.1145/2909428.2909431.
J. S. Hesthaven; S. Zhang : On the use of ANOVA expansions in reduced basis methods for high-dimensional parametric partial differential equations; Journal of Scientific Computing. 2016. DOI : 10.1007/s10915-016-0194-9.
2015
J. S. Hesthaven; G. Rozza; B. Stamm : Certified Reduced Basis Methods for Parametrized Partial Differential Equations ; Springer Verlag.
F. Negri / A. Quarteroni; G. Rozza (Dir.) : Efficient Reduction Techniques for the Simulation and Optimization of Parametrized Systems. Lausanne, EPFL, 2015. DOI : 10.5075/epfl-thesis-6810.
J. S. Hesthaven; J.-H. Jung; A. Tesdall : Hyperbolic Problems: Theory and Computation; Journal Of Scientific Computing. 2015. DOI : 10.1007/s10915-015-0065-9.
F. Chen; J. S. Hesthaven; Y. Maday; A. S. Nielsen : An Adjoint Approach for Stabilizing the Parareal Method; Comptes rendus des séances de l'Académie des Sciences. Série A, Sciences mathématiques**. 2015.
G. E. Karniadakis; J. S. Hesthaven; I. Podlubny : Special Issue on "Fractional PDEs: Theory, Numerics, and Applications"; Journal Of Computational Physics. 2015. DOI : 10.1016/j.jcp.2015.04.007.
J. Zudrop; J. S. Hesthaven : Accuracy of high order and spectral methods for hyperbolic conservation laws with discontinuous solutions; Siam Journal on Numerical Analysis. 2015. DOI : 10.1137/140992758.
L. Qiu; W. Deng; J. S. Hesthaven : Nodal discontinuous Galerkin methods for fractional diffusion equations on 2D domain with triangular meshes; Journal of Computational Physics. 2015. DOI : 10.1016/j.jcp.2015.06.022.
F. Nobile; L. Tamellini; R. Tempone : Comparison of Clenshaw-Curtis and Leja Quasi-Optimal Sparse Grids for the Approximation of Random PDEs. 2015. International Conference on Spectral and High-Order Methods 2014 (ICOSAHOM'14), Salt Lake City, June 23-27, 2014. p. 475-482. DOI : 10.1007/978-3-319-19800-2_44.
P. Gatto; J. S. Hesthaven : Numerical approximation of the fractional Laplacian via hp-finite elements, with an application to image denoising; Journal of Scientific Computing. 2015. DOI : 10.1007/s10915-014-9959-1.
Q. Xu; J. S. Hesthaven; F. Chen : A Parareal Method for Time-fractional Differential Equations; Journal of Computational Physics. 2015. DOI : 10.1016/j.jcp.2014.11.034.
W. Deng; J. S. Hesthaven : Local discontinuous Galerkin methods for fractional ordinary differential equations; Bit Numerical Mathematics. 2015. DOI : 10.1007/s10543-014-0531-z.
S. Tirupathi; J. S. Hesthaven; Y. Liang : Modeling 3D Magma Dynamics Using a Discontinuous Galerkin Method; Communications in Computational Physics. 2015. DOI : 10.4208/cicp.090314.151214a.
S. Tirupathi; J. S. Hesthaven; Y. Liang; M. Parmentier : Multilevel and Local Timestepping Discontinuous Galerkin Methods for Magma Dynamics; Computational Geosciences. 2015. DOI : 10.1007/s10596-015-9514-7.
J. S. Hesthaven; S. Zhang; X. Zhu : Reduced basis multiscale finite element methods for elliptic problems; Multiscale Modeling and Simulation. 2015. DOI : 10.1137/120898024.
F. Chen; Q. Xu; J. S. Hesthaven : A Multi-domain Spectral Method for Time-fractional Differential Equations; Journal of Computational Physics. 2015. DOI : 10.1016/j.jcp.2014.10.016.
2014
F. Chen; J. S. Hesthaven; X. Zhu : On the Use of Reduced Basis Methods to Accelerate and Stabilize the Parareal Method. 2014. Workshop on Reduced Basis, POD and Reduced Order Methods for Model and Computational Reduction: towards Real-time Computing and Visualization', Lausanne, CH. p. 187-214. DOI : 10.1007/978-3-319-02090-7_7.
C. M. Colciago / A. Quarteroni; S. Deparis (Dir.) : Reduced Order Fluid-Structure Interaction Models for Haemodynamics Applications. Lausanne, EPFL, 2014. DOI : 10.5075/epfl-thesis-6285.
R. Munipalli; Z. Liu; X. Zhu; S. Menon; J. S. Hesthaven : Applications of Model Reduction Techniques in Aerospace Combustors. 2014. AIAA Conference.
P. Chen / A. Quarteroni; G. Rozza (Dir.) : Model Order Reduction Techniques for Uncertainty Quantification Problems. Lausanne, EPFL, 2014. DOI : 10.5075/epfl-thesis-6118.
J. S. Hesthaven : Time-domain finite element methods for Maxwell's equations in metamaterials; Siam Review. 2014.
J. Li; J. S. Hesthaven : Analysis and application of the nodal discontinuous Galerkin method for wave propagation in metamaterials; Journal Of Computational Physics. 2014. DOI : 10.1016/j.jcp.2013.11.018.
R. Munipalli; X. Zhu; S. Menon; J. S. Hesthaven : Model Reduction Opportunities in Detailed Simulations of Combustion Dynamics; Aiaa Journal. 2014.
Spectral and High Order Methods for Partial Differential Equations - ICOSAHOM 2012 ; Switzerland: Springer Verlag.
Q. Xu; J. S. Hesthaven : Discontinuous Galerkin method for fractional convection-diffusion equations; Siam Journal on Numerical Analysis. 2014. DOI : 10.1137/130918174.
J. S. Hesthaven; S. Zhang; X. Zhu : High-order multiscale finite element method for elliptic problems; Multiscale Modeling and Simulation. 2014. DOI : 10.1137/120898024.
J. S. Hesthaven; B. Stamm; S. Zhang : Efficient greedy algorithms for high-dimensional parameter spaces with applications to empirical interpolation and reduced basis methods; Mathematical Modelling and Numerical Analysis. 2014. DOI : 10.1051/m2an/2013100.
P. Cazeaux; J. S. Hesthaven : Multiscale modeling of sound propagation through the lung parenchyma; Mathematical Modelling and Numerical Analysis. 2014. DOI : 10.1051/m2an/2013093.
Q. Xu; J. S. Hesthaven : Stable multi-domain spectral penalty methods for fractional partial differential equations; Journal of Computational Physics. 2014. DOI : 10.1016/j.jcp.2013.09.041.
S. E. Field; C. R. Galley; J. S. Hesthaven; J. Kaye; M. Tiglio : Fast prediction and evaluation of gravitational waveforms using surrogate models; Physical Review X. 2014. DOI : 10.1103/PhysRevX.4.031006.
J. Beck; F. Nobile; L. Tamellini; R. Tempone : A quasi-optimal sparse grids procedure for groundwater flows. 2014. International Conference on Spectral and High-Order Methods 2012 (ICOSAHOM'12), Gammarth, Tunisia, June 25-29, 2012. p. 1-16. DOI : 10.1007/978-3-319-01601-6_1.
2013
S. Chun; J. S. Hesthaven : High-order accurate methods for solving Maxwell's equations: Applications to photonic crystals and thin layer coatings ; Saarbrucken, Germany: Scholar-Press.
F. Chen; J. S. Hesthaven; X. Zhu : On the use of reduced basis methods to accelerate and stabilize the Parareal method; Reduced Order Methods for modeling and computational reduction; Milano: Springer Publishing, 2013. p. 187-214.
W. Deng; J. S. Hesthaven : Local discontinuous Galerkin methods for fractional diffusion equations; Mathematical Modelling and Numerical Analysis. 2013. DOI : 10.1051/m2an/2013091.
K. Shahbazi; J. S. Hesthaven; X. Zhu : Multi-dimensional hybrid Fourier continuation-WENO solvers for conservation laws; Journal of Computational Physics. 2013. DOI : 10.1016/j.jcp.2013.07.009.
A. C. Narayan; J. S. Hesthaven : A generalization of the Wiener rational basis functions on infinite intervals, Part II - Numerical investigation; Journal of Computational and Applied Mathematics. 2013. DOI : 10.1016/j.cam.2012.06.036.
J. S. Hesthaven : Spectral methods: algorithms, analysis and applications [book review of MR2867779]; SIAM Review. 2013.
2012
A. Kloeckner; T. Warburton; J. S. Hesthaven : High-Order Discontinuous Galerkin Methods by GPU Metaprogramming; GPU Solutions to Multi-scale Problems in Science and Engineering; Springer Verlag, 2012.
Special Issue in Memory of Professor David Gottlieb ; France: SMAI Publications.
A. Klöckner; T. Warburton; J. S. Hesthaven : Solving Wave Equations on Unstructured Geometries; GPU Computing Gems Jade Edition; Morgan Kaufmann, 2012. p. 225–242.
A. L. Tampos; J. E. C. Lope; J. S. Hesthaven : Accurate reconstruction of discontinuous functions using the singular pade-chebyshev method; IAENG International Journal of Applied Mathematics. 2012.
Enseignement & Phd
Enseignement
- Mathematics,
Programmes doctoraux
- Doctoral Program in Mathematics
- Doctoral Program in Physics
Doctorants
Bigoni Caterina
Bonev Boris
Discacciati Niccolo'
Mönkeberg Fabian
Ripamonti Nicolò
Sivak Iryna
Nielsen Allan Svejstrup ...
Bonev Boris
Discacciati Niccolo'
Mönkeberg Fabian
Ripamonti Nicolò
Sivak Iryna
A dirigé les thèses de
Maboudi Afkham Babak ...Nielsen Allan Svejstrup ...
Cours
Numerical methods for conservation laws
Introduction au développement, à l'analyse et l'application de méthodes numériques pour la résolution de lois de conservations, en mettant l'accent sur les méthodes de volumes finis et Galerkin discontinues. 