Jan S. Hesthaven
Doyen de la faculté SB
jan.hesthaven@epfl.ch +41 21 693 33 02
EPFL SB-DO
PH A2 364 (Bâtiment PH)
Station 3
CH-1015 Lausanne
+41 21 693 33 02
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 Infoscience
Jan S Hesthaven publications
2020
I. Mekkaoui; J. Pousin; J. S. Hesthaven; J.-R. Li : Effective diffusion tensor measured by diffusion MRI of moving and deforming domains; Journal of Magnetic Resonance. 2020.
2019
K. Shukla; J. M. Carcione; J. S. Hesthaven; E. L'heureux : Waves at a fluid-solid interface: Explicit versus implicit formulation of boundary conditions using a discontinuous Galerkin method. 2019-12-23.
F. Pind; C.-H. Jeong; J. S. Hesthaven; A. Engsig-Karup; J. Stromann-Andersen : Modeling extended-reaction boundary conditions in time-domain wave-based simulations of room acoustics. 2019-10-31.
X. Wan; W.-S. Don; Z. Gao; J. S. Hesthaven : An edge detector based on artificial neural network with application to hybrid Compact-WENO finite difference schemes. 2019-10-20.
J. S. Hesthaven; F. Mönkeberg : Two-dimensional RBF-ENO method on unstructured grids. 2019-10-20.
Q. Wang; N. Ripamonti; J. S. Hesthaven : Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism; Journal of Computational Physics. 2019-08-18.
Z. Zhang; M. Guo; J. S. Hesthaven : Model order reduction for large-scale structures with local nonlinearities; Computer Methods In Applied Mechanics and Engineering. 2019-08-15. DOI : 10.1016/j.cma.2019.04.042.
M. Hajihassanpour; B. Bonev; J. S. Hesthaven : A comparative study of earthquake source models in high- order accurate tsunami simulations; Ocean Modelling. 2019-08-14. DOI : 10.1016/j.ocemod.2019.101429.
J. S. Hesthaven; F. Monkeberg : Entropy Stable Essentially Nonoscillatory Methods Based On Rbf Reconstruction; Esaim-Mathematical Modelling And Numerical Analysis-Modelisation Mathematique Et Analyse Numerique. 2019-06-21. DOI : 10.1051/m2an/2019011.
F. Pind; A. P. Engsig-Karup; C.-H. Jeong; J. S. Hesthaven; M. S. Mejling et al. : Time domain room acoustic simulations using the spectral element method; Journal Of The Acoustical Society Of America. 2019-06-01. DOI : 10.1121/1.5109396.
J. Magiera; D. Ray; J. S. Hesthaven; C. Rohde : MATHICSE Technical Report: Constraint-Aware Neural Networks for Riemann Problems. 2019-04-28.
F. Pind; A. P. Engsig-Karup; C.-H. Jeong; J. S. Hesthaven; M. S. Meiling et al. : MATHICSE Technical Report: Time domain room acoustic simulations using a spectral element method. 2019-04-28.
C. Bigoni; J. S. Hesthaven : MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring. 2019-04-10.
M. Kast; M. Guo; J. S. Hesthaven : MATHICSE Technical Report: A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems. 2019-04-10.
N. Discacciati; J. S. Hesthaven; D. Ray : MATHICSE Technical Report: Controlling oscillations in high-order Discontinuous Galerkin schemes using artificial\ viscosity tuned by neural networks. 2019-01-28.
Z. Zhang; J. S. Hesthaven : Rare event simulation for large-scale structures with local nonlinearities. 2019.
Q. Wang; N. Ripamonti; J. S. Hesthaven : Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism. 2019.
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. 2019. DOI : 10.1111/1365-2478.12831.
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; Journal of Computational Physics. 2019. DOI : 10.1016/j.jcp.2019.03.050.
P. Cazeaux; J. S. Hesthaven : Projective multiscale time-integration for electrostatic particle-in-cell methods; Computer Physics Communications. 2019. DOI : 10.1016/j.cpc.2018.10.012.
2018
J. S. Hesthaven; F. Mönkeberg; S. Zaninelli : RBF Based CWENO Method. 2018-11-09. ICOSAHOM 2018, London, UK.
D. Ray; J. S. Hesthaven : Detecting troubled-cells on two-dimensional unstructured grids using a neural network; Journal of Computational Physics. 2018-11-01. DOI : 10.1016/j.jcp.2019.07.043.
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.
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.
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. 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.
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 : 10.1137/140955070.
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.
M. Azaiez; H. El Fekih; J. S. Hesthaven : Spectral and High Order Methods for Partial Differential Equations - ICOSAHOM 2012. 2014.
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.
