Massachusetts Institute of Technology Aerospace Computational Design Laboratory | AeroAstro | MIT

Benjamin Peherstorfer

PostDoc, working with Prof. Karen Willcox
Department of Aeronautics & Astronautics
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139

E-mail: pehersto at mit.edu
Office: Rm 37-431 (map)
Phone: (617) 253-7831
     

Research interests

  • Scientific computing, numerical linear algebra
  • Model reduction, multifidelity methods
  • Machine learning
  • High-dimensional problems, sparse grids
  • Bayesian inference, uncertainty propagation

News

Aug 2016:   Invited presentation at workshop on Next Generation Mobility Modeling and Simulation, UW-Madison
Jul 2016:   Co-organizer of minisymposium on model reduction at SIAM Annual Meeting 2016
Mar 2016:   Co-organizer of the workshop on data-driven model reduction and machine learning
Nov 2015:   Invited talk in the seminar series of the Transregional Collaborative Research Center on Invasive Computing
Mar 2015:   Co-organizer of minisymposium on adaptive model reduction at SIAM CSE 15
Dec 2014:   I was awarded the Heinz Schwärtzel prize for my PhD thesis
Dec 2014:   Invited talk in the scientific computing colloquium at TUM
Apr 2014:   Co-organizer of minisymposium on density estimation at SIAM UQ 14
Sep 2013:   Co-organizer of the workshop on adapt./local. MOR with machine learning

Selected preprints

[1] Peherstorfer, B., Willcox, K. & Gunzburger, M. Optimal model management for multifidelity Monte Carlo estimation.
Technical Report, Aerospace Computational Design Laboratory TR-15-2, 2015.
Full list

Five selected publications

[1] Peherstorfer, B. & Willcox, K. Data-driven operator inference for nonintrusive projection-based model reduction.
Computer Methods in Applied Mechanics and Engineering, Elsevier, 2016. (to appear).
[2] Peherstorfer, B. & Willcox, K. Online Adaptive Model Reduction for Nonlinear Systems via Low-Rank Updates.
SIAM Journal on Scientific Computing, 37(4):A2123-A2150, SIAM, 2015.
[3] Peherstorfer, B., Zimmer, S., Zenger, C. & Bungartz, H.J. A Multigrid Method for Adaptive Sparse Grids.
SIAM Journal on Scientific Computing, 37(5):S51-S70, SIAM, 2015.
[4] Peherstorfer, B., Butnaru, D., Willcox, K. & Bungartz, H.J. Localized Discrete Empirical Interpolation Method.
SIAM Journal on Scientific Computing, 36(1):A168-A192, SIAM, 2014.
[5] Pflüger, D., Peherstorfer, B. & Bungartz, H.J. Spatially adaptive sparse grids for high-dimensional data-driven problems.
Journal of Complexity, 26(5):508-522, Academic Press, Inc., 2010.
Full list

Five selected talks

[1] Peherstorfer, B. Multifidelity Methods for Uncertainty Quantification.
In SIAM Uncertainty Quantification 2016, Lausanne, Switzerland, 2016.
[2] Peherstorfer, B. Online Adaptive Model Reduction.
In SIAM Conference on Computational Science and Engineering 2015, Salt Lake City, USA, 2015.
[3] Peherstorfer, B. Density Estimation with Adaptive Sparse Grids.
In SIAM Uncertainty Quantification 2014, Savannah, USA, 2014.
[4] Peherstorfer, B. Localized Discrete Empirical Interpolation Method.
In Second International Workshop on Model Reduction for Parametrized Systems (MoRePaS II), Schloss Reisensburg, Günzburg, Germany, 2012.
[5] Peherstorfer, B. A multigrid method for PDEs on spatially adaptive sparse grids.
In 28th GAMM-Seminar on Analysis and Numerical Methods in Higher Dimensions, Leipzig, Germany, 2012.
Full list