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Research Areas
- (Nonlinear) Model order reduction
- Reduced basis methods
- Theory and applications of neural networks
Education
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- MSc. Mathematics with Minor in Computer Science, Westfälische Wilhelms-Universität Münster
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- BSc. Mathematics with Minor in Computer Science, Rheinische Friedrich-Wilhelms-Universität Bonn
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Teaching
- Übung: Tutorial Applied Functional Analysis [102400]
(in cooperation with Julia Schleuß, Prof. Dr. Mario Ohlberger)[ - | | wöchentlich | Mi. | Julia Schleuß]
[ - | | wöchentlich | Mi. | Julia Schleuß]
[ - | | wöchentlich | Mi. | Julia Schleuß]
[ | wöchentlich | Mo. | SRZ 203 | Julia Schleuß]
- Übung: Tutorial Inverse Problems [100411]
(in cooperation with Dr. Frank Wübbeling) - Übung: Tutorial Analysis & Numeric of Differential Equations [100388]
(in cooperation with Prof. Dr. Mario Ohlberger) - Praktikum: Introduction to Numerical Programming with Python [100378]
(in cooperation with Lukas Renelt, Prof. Dr. Mario Ohlberger) - Vorlesung: Analysis & Numeric of Differential Equations [100418]
(in cooperation with Prof. Dr. Mario Ohlberger)
- Übung: Tutorial Numerical Optimization [108409]
(in cooperation with Prof. Dr. Mario Ohlberger) - Vorlesung: Numerical Optimization [108408]
(in cooperation with Prof. Dr. Mario Ohlberger)
- Praktikum: Non-linear modelling in the natural sciences [106351]
(in cooperation with Julia Schleuß, Prof. Dr. Christian Engwer, Priv.-Doz. Svetlana Gurevich, Lukas Renelt, Prof. Dr. Mario Ohlberger, Prof. Dr. André Schlichting, Prof. Dr. Andreas Heuer) - Vorlesung: Numerics for partial differential equations [106352]
(in cooperation with Prof. Dr. Christian Engwer)
- Übung: Tutorial Numerical Analysis of Partial Differential Equations II [104383]
(in cooperation with Prof. Dr. Mario Ohlberger)
- Übung: Tutorial Inverse Problems [102375]
(in cooperation with Dr. Frank Wübbeling)
- Übung: Tutorial Applied Functional Analysis [102400]
Publications
- . . ‘A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs.’ SIAM Journal on Scientific Computing 45, No. 3: A1039. doi: 10.1137/22M1493318.
- . . Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling arXiv. doi: 10.48550/ARXIV.2302.14526. [submitted / under review]
- . . ‘Nonlinear Model Order Reduction using Diffeomorphic Transformations of a Space-Time Domain.’ ARGESIM Reports 17. doi: 10.11128/arep.17.a17129.
- . . ‘Adaptive machine learning based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery.’ Advances in Computational Mathematics 2022, No. 48: 73. doi: 10.1007/s10444-022-09981-z.
Talks
Practical Talks
- Kleikamp, Hendrik (): ‘Model order reduction with artificial neural networks in pyMOR’. Minitutorial on "pyMOR - Model Order Reduction with Python" at SIAM CSE (SIAM Conference on Computational Science and Engineering) 2023 (SIAM - Society for Industrial and Applied Mathematics), Amsterdam, .
Scientific Talks
- Kleikamp, Hendrik (): ‘Nonlinear model order reduction for parametrized transport-dominated PDEs using registration-based methods’. YMMOR - Young Mathematicians in Model Order Reduction, Ulm, .
Practical Talks
- Kleikamp, Hendrik (): ‘Model order reduction using artificial neural networks’. pyMOR School 2022, Magdeburg (online), .
Scientific Talks
- Kleikamp, Hendrik (): ‘Nonlinear model order reduction for hyperbolic conservation laws by means of diffeomorphic transformations of space-time domains’. Model Reduction and Surrogate Modeling (MORE), Berlin, .
- Kleikamp, Hendrik (): ‘Nonlinear model order reduction for parametrized hyperbolic conservation laws in a space-time domain’. Minisymposium on “Numerical methods for wave propagation problems” at CMAM (Computational Methods in Applied Mathematics) 2022, Wien, .
- Kleikamp, Hendrik (): ‘Nonlinear Model Order Reduction using Diffeomorphic Transformations of a Space-Time Domain’. Minisymposium on "Recent Advances in Model Reduction and Surrogate Modeling" at MATHMOD (International Conference on Mathematical Modelling) 2022, Wien, .
- Kleikamp, Hendrik (): ‘A certified and adaptive RB-ML-ROM surrogate approach for parametrized PDEs’. YMMOR - Young Mathematicians in Model Order Reduction, Münster, .
- Pelling, Art; Kleikamp, Hendrik (): ‘Introduction to System Theory and Model Order Reduction’. YMMOR - Young Mathematicians in Model Order Reduction, Münster, .
- Kleikamp, Hendrik (): ‘A certified and adaptive RB-ML-ROM surrogate approach for parametrized PDEs’. HCM Workshop: Synergies between Data Science and PDE Analysis (Hausdorff Center for Mathematics), Bonn, .
- Kleikamp, Hendrik (): ‘Nonlinear Model Order Reduction Using Geodesic Shooting in the Diffeomorphism Group’. Minisymposium on "Nonlinear Model Reduction Methods for Random or Parametric Time Dependent Problems" at SIAM UQ (SIAM Conference on Uncertainty Quantification) 2022 (SIAM - Society for Industrial and Applied Mathematics), Atlanta, Georgia (hybrid), .
- Kleikamp, Hendrik (): ‘Model order reduction using artificial neural networks’. pyMOR School 2021, Münster, .