Eurika Kaiser

1.8k total citations · 2 hit papers
25 papers, 912 citations indexed

About

Eurika Kaiser is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Eurika Kaiser has authored 25 papers receiving a total of 912 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Mechanics, 11 papers in Statistical and Nonlinear Physics and 6 papers in Artificial Intelligence. Recurrent topics in Eurika Kaiser's work include Model Reduction and Neural Networks (10 papers), Fluid Dynamics and Turbulent Flows (7 papers) and Wind and Air Flow Studies (4 papers). Eurika Kaiser is often cited by papers focused on Model Reduction and Neural Networks (10 papers), Fluid Dynamics and Turbulent Flows (7 papers) and Wind and Air Flow Studies (4 papers). Eurika Kaiser collaborates with scholars based in United States, France and Germany. Eurika Kaiser's co-authors include Steven L. Brunton, J. Nathan Kutz, Bingni W. Brunton, Joshua L. Proctor, Marko Budišić, Bernd R. Noack, Siniša Krajnović, Hui Li, Urban Fasel and Shanwu Li and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of Fluid Mechanics.

In The Last Decade

Eurika Kaiser

24 papers receiving 887 citations

Hit Papers

Chaos as an intermittently forced linear system 2017 2026 2020 2023 2017 2022 100 200 300
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. Chaos as an intermittently forced linear system
    2017 343 citations Steven L. Brunton, Bingni W. Brunton et al. Nature Communications profile →
  2. Modern Koopman Theory for Dynamical Systems
    2022 257 citations Steven L. Brunton, Marko Budišić et al. SIAM Review profile →

Peers

Eurika Kaiser
Jean-Christophe Loiseau France
Bethany Lusch United States
Jonathan H. Tu United States
Samuel Rudy United States
Marko Budišić United States
Matthew O. Williams United States
Youngsoo Choi United States
Hayden Schaeffer United States
Deep Ray United States
Bing Yu China
Jean-Christophe Loiseau France
Eurika Kaiser
Citations per year, relative to Eurika Kaiser Eurika Kaiser (= 1×) peers Jean-Christophe Loiseau

Countries citing papers authored by Eurika Kaiser

Since Specialization
Citations

This map shows the geographic impact of Eurika Kaiser'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 Eurika Kaiser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eurika Kaiser more than expected).

Fields of papers citing papers by Eurika Kaiser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eurika Kaiser. 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 Eurika Kaiser. The network helps show where Eurika Kaiser may publish in the future.

Co-authorship network of co-authors of Eurika Kaiser

This figure shows the co-authorship network connecting the top 25 collaborators of Eurika Kaiser. A scholar is included among the top collaborators of Eurika Kaiser 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 Eurika Kaiser. Eurika Kaiser 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.
Kaiser, Eurika, et al.. (2025). Separation of periodic orbits in the delay-embedded space of chaotic attractors. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 481(2322).
2.
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
3.
Brunton, Steven L., Marko Budišić, Eurika Kaiser, & J. Nathan Kutz. (2022). Modern Koopman Theory for Dynamical Systems. SIAM Review. 64(2). 229–340. 257 indexed citations breakdown →
4.
Fasel, Urban, Eurika Kaiser, J. Nathan Kutz, Bingni W. Brunton, & Steven L. Brunton. (2021). SINDy with Control: A Tutorial. 2021 60th IEEE Conference on Decision and Control (CDC). 16–21. 43 indexed citations
5.
Sierra, Carlos A., Holger Metzler, Markus M. Müller, & Eurika Kaiser. (2021). Closed-loop and congestion control of the global carbon-climate system. Climatic Change. 165(1-2). 5 indexed citations
6.
Kaiser, Eurika, J. Nathan Kutz, & Steven L. Brunton. (2020). De-entanglement of complex flows with time delay coordinates. Bulletin of the American Physical Society. 1 indexed citations
7.
Niven, Robert K., Laurent Cordier, Eurika Kaiser, Michael Schlegel, & Bernd R. Noack. (2020). New Conservation Laws Based on Generalised Reynolds Transport Theorems. HAL (Le Centre pour la Communication Scientifique Directe). 3 indexed citations
8.
Kaiser, Eurika, et al.. (2020). Deep reinforcement learning for optical systems: A case study of mode-locked lasers. Machine Learning Science and Technology. 1(4). 45013–45013. 21 indexed citations
9.
Li, Shanwu, Eurika Kaiser, Shujin Laima, et al.. (2019). Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems. Physical review. E. 100(2). 22220–22220. 51 indexed citations
10.
Semaan, Richard, et al.. (2019). Cluster‐based network model for drag reduction mechanisms of an actuated turbulent boundary layer. PAMM. 19(1). 2 indexed citations
11.
Nair, Aditya, C. Yeh, Eurika Kaiser, et al.. (2019). Cluster-based feedback control of turbulent post-stall separated flows. Journal of Fluid Mechanics. 875. 345–375. 52 indexed citations
12.
Brunton, Steven L., et al.. (2017). Koopman operator theory: Past, present, and future. Bulletin of the American Physical Society. 2 indexed citations
13.
Brunton, Steven L., Bingni W. Brunton, Joshua L. Proctor, Eurika Kaiser, & J. Nathan Kutz. (2017). Chaos as an intermittently forced linear system. Nature Communications. 8(1). 19–19. 343 indexed citations breakdown →
14.
Li, Ruiying, Bernd R. Noack, Laurent Cordier, et al.. (2017). Linear genetic programming control for strongly nonlinear dynamics with frequency crosstalk. SHILAP Revista de lepidopterología. 3 indexed citations
15.
Kaiser, Eurika, Bernd R. Noack, Andreas Spohn, Louis N. Cattafesta, & Marek Morzyński. (2017). Cluster-based control of a separating flow over a smoothly contoured ramp. Theoretical and Computational Fluid Dynamics. 31(5-6). 579–593. 10 indexed citations
16.
Kaiser, Eurika, Marek Morzyński, Guillaume Daviller, et al.. (2017). Sparsity enabled cluster reduced-order models for control. Journal of Computational Physics. 352. 388–409. 16 indexed citations
17.
Kaiser, Eurika, et al.. (2015). Cluster-based reduced-order modelling of the flow in the wake of a high speed train. Journal of Wind Engineering and Industrial Aerodynamics. 145. 327–338. 43 indexed citations
18.
Kaiser, Eurika, Bernd R. Noack, Laurent Cordier, et al.. (2014). Cluster-based reduced-order modelling of shear flows. AIP conference proceedings. 1636. 151–158. 8 indexed citations
19.
Kaiser, Eurika, et al.. (2014). Cluster-based analysis of cycle-to-cycle variations: application to internal combustion engines. Experiments in Fluids. 55(11). 24 indexed citations
20.
Kaiser, Eurika, Bernd R. Noack, Laurent Cordier, et al.. (2013). Cluster-based reduced-order modelling of a mixing layer. publish.UP (University of Potsdam). 1 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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