D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 53 Citations 14,551 191 World Ranking 1236 National Ranking 530

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Artificial intelligence
  • Statistics

His main research concerns Nonlinear system, Dynamical systems theory, Applied mathematics, Dynamic mode decomposition and Artificial intelligence. His studies in Nonlinear system integrate themes in fields like Linear system, Control engineering, Turbulence, Interpretability and Series. His Dynamical systems theory research integrates issues from Theoretical computer science, Dynamical system, Model selection, Lorenz system and Complex system.

His work carried out in the field of Complex system brings together such families of science as Data-driven and Compressed sensing. The study incorporates disciplines such as Partial differential equation, Sparse regression, Galerkin method and Dimensionality reduction in addition to Applied mathematics. His studies deal with areas such as Robust principal component analysis and Algorithm, Singular value decomposition as well as Dynamic mode decomposition.

His most cited work include:

  • Discovering governing equations from data by sparse identification of nonlinear dynamical systems (1065 citations)
  • On dynamic mode decomposition: Theory and applications (712 citations)
  • Modal Analysis of Fluid Flows: An Overview (475 citations)

What are the main themes of his work throughout his whole career to date?

Nonlinear system, Algorithm, Artificial intelligence, Dynamical systems theory and Dynamic mode decomposition are his primary areas of study. His work in Nonlinear system tackles topics such as Applied mathematics which are related to areas like Operator and Partial differential equation. The various areas that he examines in his Algorithm study include Fluid dynamics, Matrix, Sampling and Dimensionality reduction.

Steven L. Brunton combines subjects such as Machine learning, Computer vision and Pattern recognition with his study of Artificial intelligence. His study explores the link between Dynamical systems theory and topics such as Theoretical computer science that cross with problems in Complex system. His Dynamic mode decomposition research incorporates themes from Singular value decomposition, Operator theory, Eigenvalues and eigenvectors and System identification.

He most often published in these fields:

  • Nonlinear system (28.53%)
  • Algorithm (17.73%)
  • Artificial intelligence (16.62%)

What were the highlights of his more recent work (between 2019-2021)?

  • Nonlinear system (28.53%)
  • Dynamic mode decomposition (16.07%)
  • Dynamical systems theory (16.34%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Nonlinear system, Dynamic mode decomposition, Dynamical systems theory, Statistical physics and Algorithm. His Nonlinear system research incorporates elements of Flow, Model predictive control, Data-driven, Applied mathematics and System identification. His Flow study combines topics in areas such as Forcing, Chaotic, Turbulence, System dynamics and Wake.

His Dynamic mode decomposition research includes themes of Basis, Bilinear interpolation, Singular value decomposition, Linear model and Vorticity. His work deals with themes such as Theoretical computer science, Parametric statistics, Sampling, Deep learning and Range, which intersect with Dynamical systems theory. The Algorithm study combines topics in areas such as Identification, Dynamical system, Model selection, Matrix decomposition and Robustness.

Between 2019 and 2021, his most popular works were:

  • Machine Learning for Fluid Mechanics (347 citations)
  • Modal Analysis of Fluid Flows: Applications and Outlook (106 citations)
  • Randomized CP Tensor Decomposition (23 citations)

In his most recent research, the most cited papers focused on:

  • Quantum mechanics
  • Artificial intelligence
  • Statistics

His primary scientific interests are in Nonlinear system, Algorithm, Artificial intelligence, Dynamical systems theory and Fluid dynamics. His Nonlinear system research includes elements of Physical system, System identification, Applied mathematics and Dynamic mode decomposition. His biological study spans a wide range of topics, including Computational physics, Operator theory, Overfitting and Observable.

His Algorithm study integrates concerns from other disciplines, such as Identification, Dynamical system, Partial differential equation, Model selection and Dimensionality reduction. His Deep learning study, which is part of a larger body of work in Artificial intelligence, is frequently linked to Network architecture, bridging the gap between disciplines. His Dynamical systems theory study incorporates themes from Range, Probability and statistics, Linear algebra and Big data.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Steven L. Brunton;Joshua L. Proctor;J. Nathan Kutz.
Proceedings of the National Academy of Sciences of the United States of America (2016)

1196 Citations

On dynamic mode decomposition: Theory and applications

Jonathan H. Tu;Clarence Worth Rowley;Dirk M. Luchtenburg;Steven L. Brunton.
ACM Journal of Computer Documentation (2014)

848 Citations

Modal Analysis of Fluid Flows: An Overview

Kunihiko Taira;Steven L. Brunton;Scott T. M. Dawson;Clarence W. Rowley.
AIAA Journal (2017)

612 Citations

Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems

J. Nathan Kutz;Steven L. Brunton;Bingni W. Brunton;Joshua L. Proctor.
(2016)

560 Citations

Data-driven discovery of partial differential equations.

Samuel H. Rudy;Steven L. Brunton;Joshua L. Proctor;J. Nathan Kutz.
Science Advances (2017)

514 Citations

Machine Learning for Fluid Mechanics

Steven L. Brunton;Bernd R. Noack;Bernd R. Noack;Petros Koumoutsakos.
Annual Review of Fluid Mechanics (2020)

381 Citations

Maximum Power Point Tracking for Photovoltaic Optimization Using Ripple-Based Extremum Seeking Control

Steven L Brunton;Clarence W Rowley;Sanjeev R Kulkarni;Charles Clarkson.
IEEE Transactions on Power Electronics (2010)

371 Citations

Dynamic Mode Decomposition with Control

Joshua L. Proctor;Steven L. Brunton;J. Nathan Kutz.
Siam Journal on Applied Dynamical Systems (2016)

365 Citations

Closed-Loop Turbulence Control: Progress and Challenges

Steven L. Brunton;Bernd R. Noack.
Applied Mechanics Reviews (2015)

333 Citations

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

Steven L. Brunton;J. Nathan Kutz.
(2019)

312 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Steven L. Brunton

Bernd R. Noack

Bernd R. Noack

Harbin Institute of Technology

Publications: 76

J. Nathan Kutz

J. Nathan Kutz

University of Washington

Publications: 48

David R. Smith

David R. Smith

Duke University

Publications: 33

George Em Karniadakis

George Em Karniadakis

Brown University

Publications: 32

Clarence W. Rowley

Clarence W. Rowley

Princeton University

Publications: 31

Christof Schütte

Christof Schütte

Zuse Institute Berlin

Publications: 28

Ioannis G. Kevrekidis

Ioannis G. Kevrekidis

Johns Hopkins University

Publications: 25

Francisco Chinesta

Francisco Chinesta

ESI (France)

Publications: 23

Gianluigi Rozza

Gianluigi Rozza

International School for Advanced Studies

Publications: 21

Elías Cueto

Elías Cueto

University of Zaragoza

Publications: 20

Karen Willcox

Karen Willcox

The University of Texas at Austin

Publications: 20

Paris Perdikaris

Paris Perdikaris

University of Pennsylvania

Publications: 17

I. M. Navon

I. M. Navon

Florida State University

Publications: 17

Louis N. Cattafesta

Louis N. Cattafesta

Florida State University

Publications: 16

Philipp Schlatter

Philipp Schlatter

Royal Institute of Technology

Publications: 14

Mehran Mesbahi

Mehran Mesbahi

University of Washington

Publications: 14

Something went wrong. Please try again later.