Kathleen Champion
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- Model Reduction and Neural Networks 3
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- Probabilistic and Robust Engineering Design 2
- Control and Systems Engineering top 10%
- Control Systems and Identification 1
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- Computational Physics and Python Applications 1
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- Fluid Dynamics and Vibration Analysis 1
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- Neural dynamics and brain function 1
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- Photoreceptor and optogenetics research 1
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- Advanced Image Processing Techniques 1
- Co-authors
- Steven L. BruntonJ. Nathan KutzBrian M. de SilvaJean-Christophe LoiseauMarkus QuadeJared CallahamCharles B. DelahuntKadierdan Kaheman
- Cited by
- Statistical and Nonlinear PhysicsStatistics, Probability and UncertaintyControl and Systems Engineering
- Journals
- SIAM Journal on Applied Dynamical Systems (1 paper)Communications Biology (1 paper)The Journal of Open Source Software (2 papers)
- Partner nations
- United StatesFrance
In The Last Decade
Kathleen Champion
4 papers receiving 328 citations
Hit Papers
Peers
Comparison fields: 5 of 63
- Statistical and Nonlinear Physics 221
- Statistics, Probability and Uncertainty 75
- Control and Systems Engineering 95
- Artificial Intelligence 82
- Computational Mechanics 52
Countries citing papers authored by Kathleen Champion
This map shows the geographic impact of Kathleen Champion'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 Kathleen Champion with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kathleen Champion more than expected).
Fields of papers citing papers by Kathleen Champion
This network shows the impact of papers produced by Kathleen Champion. 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 Kathleen Champion. The network helps show where Kathleen Champion may publish in the future.
Co-authorship network
The 13 scholars most cited alongside Kathleen Champion, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | PySINDy: A comprehensive Python package for robust sparse system identificationbreakdown → | 2022 | 105 |
| 3 | 2020 | 126 | |
| 4 | 2019 | 107 |
About Kathleen Champion
Kathleen Champion is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics, Cellular and Molecular Neuroscience, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 4 papers that have together received 339 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (3 papers), Probabilistic and Robust Engineering Design (2 papers), Neural dynamics and brain function (1 paper), Photoreceptor and optogenetics research (1 paper), Control Systems and Identification (1 paper), Computational Physics and Python Applications (1 paper), Fluid Dynamics and Vibration Analysis (1 paper) and Advanced Image Processing Techniques (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (221 citations), Statistics, Probability and Uncertainty (75 citations), Control and Systems Engineering (95 citations), Artificial Intelligence (82 citations) and Computational Mechanics (52 citations). Kathleen Champion has collaborated with scholars based in United States and France. Frequent co-authors include Steven L. Brunton, J. Nathan Kutz, Brian M. de Silva, Jean-Christophe Loiseau, Markus Quade, Jared Callaham, Charles B. Delahunt, Kadierdan Kaheman, Alan A. Kaptanoglu and Zachary G. Nicolaou. Their work appears in journals such as SIAM Journal on Applied Dynamical Systems, Communications Biology and The Journal of Open Source Software.
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.