Steven L. Brunton

28.8k total citations · 19 hit papers
212 papers, 16.9k citations indexed

About

Steven L. Brunton is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Steven L. Brunton has authored 212 papers receiving a total of 16.9k indexed citations (citations by other indexed papers that have themselves been cited), including 120 papers in Statistical and Nonlinear Physics, 80 papers in Computational Mechanics and 39 papers in Aerospace Engineering. Recurrent topics in Steven L. Brunton's work include Model Reduction and Neural Networks (113 papers), Fluid Dynamics and Turbulent Flows (50 papers) and Probabilistic and Robust Engineering Design (32 papers). Steven L. Brunton is often cited by papers focused on Model Reduction and Neural Networks (113 papers), Fluid Dynamics and Turbulent Flows (50 papers) and Probabilistic and Robust Engineering Design (32 papers). Steven L. Brunton collaborates with scholars based in United States, France and Germany. Steven L. Brunton's co-authors include J. Nathan Kutz, Joshua L. Proctor, Bingni W. Brunton, Clarence W. Rowley, Samuel Rudy, Bernd R. Noack, Bethany Lusch, Kunihiko Taira, Scott T. M. Dawson and Ricardo Vinuesa and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Steven L. Brunton

207 papers receiving 16.4k citations

Hit Papers

Discovering governing equ... 2015 2026 2018 2022 2016 2017 2017 2018 2019 500 1000 1.5k 2.0k 2.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Discovering governing equations from data by sparse identification of nonlinear dynamical systems
    2016 2.6k citations Steven L. Brunton, Joshua L. Proctor et al. profile →
  2. Modal Analysis of Fluid Flows: An Overview
    2017 1.2k citations Kunihiko Taira, Steven L. Brunton et al. AIAA Journal profile →
  3. Data-driven discovery of partial differential equations
    2017 931 citations Steven L. Brunton, Joshua L. Proctor et al. profile →
  4. Deep learning for universal linear embeddings of nonlinear dynamics
    2018 793 citations J. Nathan Kutz, Steven L. Brunton et al. Nature Communications profile →
  5. Data-Driven Science and Engineering
    2019 710 citations Steven L. Brunton, J. Nathan Kutz profile →
  6. Dynamic Mode Decomposition
    2016 689 citations J. Nathan Kutz, Steven L. Brunton et al. Society for Industrial and Applied Mathematics eBooks profile →
  7. Dynamic Mode Decomposition with Control
    2016 611 citations Joshua L. Proctor, Steven L. Brunton et al. profile →
  8. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems
    2016 434 citations J. Nathan Kutz, Steven L. Brunton et al. profile →
  9. Closed-Loop Turbulence Control: Progress and Challenges
    2015 408 citations Steven L. Brunton et al. profile →
  10. Modal Analysis of Fluid Flows: Applications and Outlook
    2019 406 citations Kunihiko Taira, Steven L. Brunton et al. AIAA Journal profile →
  11. Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control
    2016 355 citations Steven L. Brunton, Bingni W. Brunton et al. profile →
  12. Chaos as an intermittently forced linear system
    2017 343 citations Steven L. Brunton, Bingni W. Brunton et al. Nature Communications profile →
  13. Enhancing computational fluid dynamics with machine learning
    2022 330 citations Steven L. Brunton et al. profile →
  14. Data-Driven Science and Engineering
    2022 318 citations Steven L. Brunton et al. profile →
  15. Modern Koopman Theory for Dynamical Systems
    2022 257 citations Steven L. Brunton, Eurika Kaiser et al. profile →
  16. Generalizing Koopman Theory to Allow for Inputs and Control.
    2018 233 citations Joshua L. Proctor, Steven L. Brunton et al. profile →
  17. Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control
    2022 167 citations Urban Fasel, J. Nathan Kutz et al. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences profile →
  18. PySINDy: A comprehensive Python package for robust sparse system identification
    2022 105 citations Alan A. Kaptanoglu, Brian M. de Silva et al. The Journal of Open Source Software profile →
  19. Physics-informed dynamic mode decomposition
    2023 87 citations Beverley McKeon, J. Nathan Kutz et al. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Steven L. Brunton United States 53 8.8k 5.8k 3.1k 2.9k 2.5k 212 16.9k
J. Nathan Kutz United States 58 9.2k 1.0× 3.9k 0.7× 2.8k 0.9× 1.8k 0.6× 2.4k 1.0× 341 18.2k
Paris Perdikaris United States 37 10.6k 1.2× 4.5k 0.8× 1.5k 0.5× 2.5k 0.8× 3.6k 1.4× 79 20.4k
Maziar Raissi United States 15 7.8k 0.9× 3.3k 0.6× 1.1k 0.4× 1.7k 0.6× 2.5k 1.0× 32 14.4k
Karen Willcox United States 45 5.6k 0.6× 3.1k 0.5× 1.3k 0.4× 1.6k 0.6× 880 0.3× 252 15.1k
Ioannis G. Kevrekidis United States 59 5.3k 0.6× 3.3k 0.6× 1.5k 0.5× 820 0.3× 1.7k 0.7× 398 17.4k
Igor Mezić United States 42 5.1k 0.6× 3.5k 0.6× 1.6k 0.5× 1.1k 0.4× 689 0.3× 219 12.2k
Jerrold E. Marsden United States 90 10.8k 1.2× 6.6k 1.1× 8.2k 2.6× 2.4k 0.8× 581 0.2× 406 33.3k
Peter J. Schmid France 42 3.8k 0.4× 9.2k 1.6× 854 0.3× 3.5k 1.2× 328 0.1× 178 12.1k
Sifan Wang United States 11 3.9k 0.4× 1.7k 0.3× 505 0.2× 1.0k 0.3× 1.3k 0.5× 21 7.1k
Max Gunzburger United States 65 1.9k 0.2× 7.9k 1.4× 1.0k 0.3× 733 0.3× 346 0.1× 333 14.9k

Countries citing papers authored by Steven L. Brunton

Since Specialization
Citations

This map shows the geographic impact of Steven L. Brunton's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Steven L. Brunton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven L. Brunton more than expected).

Fields of papers citing papers by Steven L. Brunton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven L. Brunton. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Steven L. Brunton. The network helps show where Steven L. Brunton may publish in the future.

Co-authorship network of co-authors of Steven L. Brunton

This figure shows the co-authorship network connecting the top 25 collaborators of Steven L. Brunton. A scholar is included among the top collaborators of Steven L. Brunton based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Steven L. Brunton. Steven L. Brunton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Brunton, Steven L., et al.. (2024). An experimental evaluation of the interplay between geometry and scale on cross-flow turbine performance. Renewable and Sustainable Energy Reviews. 206. 114848–114848. 7 indexed citations
2.
Peitz, Sebastian, et al.. (2024). Distributed control of partial differential equations using convolutional reinforcement learning. Physica D Nonlinear Phenomena. 461. 134096–134096. 13 indexed citations
3.
Sholokhov, Aleksei, Saleh Nabi, Joshua Rapp, et al.. (2024). Single-Pixel Imaging of Spatio-Temporal Flows Using Differentiable Latent Dynamics. IEEE Transactions on Computational Imaging. 10. 1124–1138. 1 indexed citations
4.
Brunton, Steven L., et al.. (2024). Lagrangian gradient regression for the detection of coherent structures from sparse trajectory data. Royal Society Open Science. 11(10). 240586–240586. 2 indexed citations
5.
Pan, Shaowu, Eurika Kaiser, Brian M. de Silva, J. Nathan Kutz, & Steven L. Brunton. (2024). PyKoopman: A Python Package for Data-DrivenApproximation of the Koopman Operator. The Journal of Open Source Software. 9(94). 5881–5881. 7 indexed citations
6.
Ouala, Said, Steven L. Brunton, Bertrand Chapron, et al.. (2023). Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning. Physica D Nonlinear Phenomena. 446. 133630–133630. 7 indexed citations
7.
Lore, J., S. De Pascuale, Jae-Sun Park, et al.. (2023). Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *. Nuclear Fusion. 63(4). 46015–46015. 14 indexed citations
8.
Fasel, Urban, J. Nathan Kutz, Bingni W. Brunton, & Steven L. Brunton. (2022). Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 478(2260). 20210904–20210904. 167 indexed citations breakdown →
9.
Kaptanoglu, Alan A., Brian M. de Silva, Urban Fasel, et al.. (2022). PySINDy: A comprehensive Python package for robust sparse system identification. The Journal of Open Source Software. 7(69). 3994–3994. 105 indexed citations breakdown →
10.
Callaham, Jared, et al.. (2021). Learning dominant physical processes with data-driven balance models. Nature Communications. 12(1). 1016–1016. 52 indexed citations
11.
Shea, Daniel E., Rajiv Giridharagopal, David S. Ginger, Steven L. Brunton, & J. Nathan Kutz. (2021). Extraction of Instantaneous Frequencies and Amplitudes in Nonstationary Time-Series Data. IEEE Access. 9. 83453–83466. 6 indexed citations
12.
Brunton, Steven L., et al.. (2021). Data-driven modeling of rotating detonation waves. Physical Review Fluids. 6(5). 14 indexed citations
13.
Brunton, Steven L., et al.. (2021). Deep Learning to Accelerate Scatterer-to-Field Mapping for Inverse Design of Dielectric Metasurfaces. ACS Photonics. 8(2). 481–488. 73 indexed citations
14.
Silva, Brian M. de, et al.. (2021). PySensors: A Python package for sparse sensor placement. The Journal of Open Source Software. 6(58). 2828–2828. 11 indexed citations
15.
Zheng, Peng, et al.. (2018). Sparse Relaxed Regularized Regression: SR3.. arXiv (Cornell University). 2 indexed citations
16.
Manohar, Krithika, J. Nathan Kutz, & Steven L. Brunton. (2018). Optimal Sensor and Actuator Placement using Balanced Model Reduction.. arXiv (Cornell University). 4 indexed citations
17.
Brunton, Steven L.. (2017). Discovering governing equations from data by sparse identification of nonlinear dynamics. Bulletin of the American Physical Society. 2017. 4 indexed citations
18.
Taira, Kunihiko, Steven L. Brunton, Scott T. M. Dawson, et al.. (2017). Modal Analysis of Fluid Flows: An Overview. AIAA Journal. 55(12). 4013–4041. 1234 indexed citations breakdown →
19.
Kutz, J. Nathan, Steven L. Brunton, Bingni W. Brunton, & Joshua L. Proctor. (2016). Dynamic Mode Decomposition. Society for Industrial and Applied Mathematics eBooks. 689 indexed citations breakdown →
20.
Brunton, Steven L. & Clarence W. Rowley. (2008). A Method for Fast Computation of FTLE Fields. Bulletin of the American Physical Society. 61. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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