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Jan S. Hesthaven is a Danish mathematician, currently Vice President for Academic Affairs at EPFL (École polytechnique fédérale de Lausanne). He is Professor of Mathematics, holds the Chair of Computational Mathematics and Simulation Science (MCSS), and was appointed Vice President for Academic Affairs at EPFL (starting in 2021). He is particularly known for contributions to the development, analysis and application of high-order accurate computational methods for time-dependent partial differential equations. He has also contributed substantially to the development of reduced order models and the application of neural networks and machine learning techniques to problems in science and engineering.

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  • Jan S. Hesthaven is a Danish mathematician, currently Vice President for Academic Affairs at EPFL (École polytechnique fédérale de Lausanne). He is Professor of Mathematics, holds the Chair of Computational Mathematics and Simulation Science (MCSS), and was appointed Vice President for Academic Affairs at EPFL (starting in 2021). He is particularly known for contributions to the development, analysis and application of high-order accurate computational methods for time-dependent partial differential equations. He has also contributed substantially to the development of reduced order models and the application of neural networks and machine learning techniques to problems in science and engineering. (en)
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  • Professor Jan S Hesthaven (en)
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  • (en)
  • AMS Fellow (en)
  • SIAM Fellow (en)
  • Philip J. Bray Award for Teaching Excellence (en)
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  • Prof. Hesthaven, circa 2019 (en)
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  • Computational methods for time-dependent partial differential equations (en)
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  • Jan S. Hesthaven (en)
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  • Jan S. Hesthaven is a Danish mathematician, currently Vice President for Academic Affairs at EPFL (École polytechnique fédérale de Lausanne). He is Professor of Mathematics, holds the Chair of Computational Mathematics and Simulation Science (MCSS), and was appointed Vice President for Academic Affairs at EPFL (starting in 2021). He is particularly known for contributions to the development, analysis and application of high-order accurate computational methods for time-dependent partial differential equations. He has also contributed substantially to the development of reduced order models and the application of neural networks and machine learning techniques to problems in science and engineering. (en)
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  • Jan S. Hesthaven (en)
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  • Jan S. Hesthaven (en)
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