Dr. Felix Tobias Schindler

No current affiliations available for this person. The person is no longer active at the university.

Further Profiles

Curriculum Vitae (CV)

Research Focus

Multiscale analysis of two-phase flow in porous media with complex heterogeneities
Model reduction of parametric partial differential equations
Numerical analysis of partial differential equations

Academic Education
11/2009 - 10/2015	Promotionsstudium
10/2003 - 10/2009	Studium

Publications

Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling Wenzel, Tizian; Haasdonk, Bernard; Kleikamp, Hendrik; Ohlberger, Mario; Schindler, Felix (2024) In: Lirkov, I.; Margenov, S. (eds.), Large-Scale Scientific Computations, 117-125. Cham: Springer Nature. doi:10.1007/978-3-031-56208-2_11 Research article in edited proceedings (conference) \| Peer reviewed \| Published
Adaptive Localized Reduced Basis Methods for Large Scale PDE-constrained Optimization Keil, Tim; Ohlberger, Mario; Schindler, Felix (2024) In: Lirkov, I; Margenov, S (eds.), Large-Scale Scientific Computations, 108-116. Cham: Springer Nature. doi:10.1007/978-3-031-56208-2_10 Research article in edited proceedings (conference) \| Peer reviewed \| Published
Local training and enrichment based on a residual localization strategy Tim Keil, Mario Ohlberger, Felix Schindler, Julia Schleuß (2024) In: Frolkovič, P; Mikula, K; Ševčovič, D (eds.), Proceedings of the Conference Algoritmy 2024, 76-84. Bratislava: / Jednota slovenských matematikov a fyzikov. Research article in edited proceedings (conference) \| Peer reviewed \| Published
A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs Haasdonk B, Kleikamp H, Ohlberger M, Schindler F, Wenzel T (2023) In: SIAM Journal on Scientific Computing, 45(3), A1039-1065. doi:10.1137/22M1493318 Research article (journal) \| Peer reviewed \| Published
A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows Gavrilenko Pavel, Haasdonk Bernard, Iliev Oleg, Ohlberger Mario, Schindler Felix, Toktaliev Pavel, Wenzel Tizian, Youssef Maha (2022) In: Lirkov Ivan, Margenov Svetozar (eds.), Large-Scale Scientific Computing, 378-386. Cham: Springer VDI Verlag. doi:10.1007/978-3-030-97549-4_43 Research article (book contribution) \| Peer reviewed \| Published

Show all publications (26)

Projects

ML-MORE: Machine learning and model order reduction to predict the efficiency of catalytic filters. Subproject 1: Model Order Reduction (ML-MORE) Duration: 01/04/2020 - 31/12/2023 Funded by: Federal Ministry of Research, Technology and Space Type of project: Participation in federally funded joint project
EXC 2044 - C4: Geometry-based modelling, approximation, and reduction Duration: 01/01/2019 - 31/12/2025 \| 1st Funding period Funded by: DFG - Cluster of Excellence Type of project: Subproject in DFG-joint project hosted at University of Münster
Localized Reduced Basis Methods for PDE-constrained Parameter Optimization (LRB-Opt) Duration: 01/01/2019 - 30/06/2023 Funded by: DFG - Individual Grants Programme Type of project: Individual project
pyMOR - Sustainable Software for Model Order Reduction (pyMOR) Duration: 01/03/2018 - 31/03/2022 Funded by: DFG - Scientific Library Services and Information Systems Type of project: Individual project
Multi-scale analysis of two-phase flow in porous media with complex heterogenities Duration: 01/03/2012 - 28/02/2013 Funded by: DFG - Individual Grants Programme Type of project: Individual project

Show all projects (6)

Talks

Locally conservative Reduced Basis methods Schindler, Felix (19/02/2019) 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics GAMM 2019, Universität Wien, Wien, Österreich Type of talk: scientific Talk
Fully certified and adaptive localized model reduction for elliptic and parabolic problems Ohlberger M, Rave S, Schindler F (10/11/2016) Recent developments in numerical methods for model reduction, Institute Henri Poincaré, Paris, France Type of talk: scientific Talk

Doctorates

Model Reduction for Parametric Multi-Scale Problems
Candidate: Schindler, Felix | Supervisors: Ohlberger, Mario
Period of time: until 23/10/2015
Doctoral examination procedure finished at: Doctoral examination procedure at University of Münster

Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling Wenzel, Tizian; Haasdonk, Bernard; Kleikamp, Hendrik; Ohlberger, Mario; Schindler, Felix (2024) In: Lirkov, I.; Margenov, S. (eds.), Large-Scale Scientific Computations, 117-125. Cham: Springer Nature. doi:10.1007/978-3-031-56208-2_11 Research article in edited proceedings (conference) \| Peer reviewed \| Published
Adaptive Localized Reduced Basis Methods for Large Scale PDE-constrained Optimization Keil, Tim; Ohlberger, Mario; Schindler, Felix (2024) In: Lirkov, I; Margenov, S (eds.), Large-Scale Scientific Computations, 108-116. Cham: Springer Nature. doi:10.1007/978-3-031-56208-2_10 Research article in edited proceedings (conference) \| Peer reviewed \| Published
Local training and enrichment based on a residual localization strategy Tim Keil, Mario Ohlberger, Felix Schindler, Julia Schleuß (2024) In: Frolkovič, P; Mikula, K; Ševčovič, D (eds.), Proceedings of the Conference Algoritmy 2024, 76-84. Bratislava: / Jednota slovenských matematikov a fyzikov. Research article in edited proceedings (conference) \| Peer reviewed \| Published
A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs Haasdonk B, Kleikamp H, Ohlberger M, Schindler F, Wenzel T (2023) In: SIAM Journal on Scientific Computing, 45(3), A1039-1065. doi:10.1137/22M1493318 Research article (journal) \| Peer reviewed \| Published
A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows Gavrilenko Pavel, Haasdonk Bernard, Iliev Oleg, Ohlberger Mario, Schindler Felix, Toktaliev Pavel, Wenzel Tizian, Youssef Maha (2022) In: Lirkov Ivan, Margenov Svetozar (eds.), Large-Scale Scientific Computing, 378-386. Cham: Springer VDI Verlag. doi:10.1007/978-3-030-97549-4_43 Research article (book contribution) \| Peer reviewed \| Published