Moore Sloan Postdoctoral Fellow

(2016-present, with J. Nathan Kutz)

​

PhD 2015, Fluid Dynamics, Universite de Poitiers (Advisor: Bernd Noack)

Thesis: Cluster-based reduced order models

​

Selected publications:

• Data-driven discovery of Koopman eigenfunctions for control (Kaiser, Kutz, Brunton)

• Sparse identification of nonlinear dynamics for model predictive control in the low-data limit (Kaiser, Kutz, Brunton)

(2019-present, with Richard Semaan)

Website: www.benjaminherrmann.com

​

PhD 2018, Fluid Dynamics, University of Chile (Advisor: Williams R. Calderon Munoz)

​

Modeling synchronization in forced turbulent oscillator flows
Benjamin Herrmann, Philipp Oswald, Richard Semaan, Steven L. Brunton
https://arxiv.org/abs/2001.12000

To appear in Communications Physics, 2020.

​

Postdoctoral Fellow

(2019-present, with J. Nathan Kutz)

​

PhD 2019, Advanced Infrastructure Systems, Carnegie Mellon (Advisor: Mario Bergés)

Thesis: Variational Methods for Energy Systems

​

Selected publications:

• Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction (Lange, Brunton, Kutz)

Postdoctoral Fellow

(2019-present, with Nathan Kutz)

​

PhD 2019, Mathematics, University of California Davis (Advisor: Raissa D’Souza)

​

​

Postdoctoral Fellow

(2020, with J. Nathan Kutz)

PhD 2020, Applied Mathematics, University of Washington (Advisors: Steven Brunton and Nathan Kutz)

Thesis: Data-driven discovery and model reduction of complex systems

​

Selected publications:

PySINDy: A Python package for the sparse identification of nonlinear dynamical systems from data (de Silva, Champion, Quade, Loiseau, Kutz, Brunton)

Discovery of Physics from Data: Universal Laws and Discrepancy Models (de Silva, Higdon, Brunton, Kutz)

PhD student (2016-present) co-advised with Eric Seibel

Selected publications:

• RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology (Gong, Erichson, Kelly, Tutoiu, Schowengerdt, Brunton, Seibel)

PhD student (2017-present), co-advised with Nathan Kutz

​

PhD student (2017-present), co-advised with Brian Polagye

Selected publications:

Robust Principal Component Analysis for Particle Image Velocimetry (Scherl, Strom, Shang, Williams, Polagye, Brunton)

​

Website: https://www.isabelscherl.com/

PhD student (2017-present)

Selected publications:

• Robust flow reconstruction from limited measurements via sparse representation (Callaham, Maeda, Brunton)

PhD student (2018-present)

​

PhD student (2018-present), co-advised with Nathan Kutz

Selected publications:

    Multiresolution Convolutional Autoencoders (Liu, Ponce, Brunton, Kutz)
 

PhD student (2019-present) co-advised with Bing Brunton

​

PhD student (2018-present) co-advised with Nathan Kutz

​

PhD student (2019-present)

Selected publications:

Characterizing Magnetized Plasmas with Dynamic Mode Decomposition (Kaptanoglu, Morgan, Hansen, Brunton)

PhD student (2019-present)

​

Graduate student (2020), co-advised with Zhuoyuan Song

​

Interlake High School, Bellevue, WA

2019-present

​

Interlake High School, Bellevue, WA

2019-present

​