Hunter Johnston
Impact in
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- Model Reduction and Neural Networks
- Numerical Analysis top 10%
- Numerical methods for differential equations
Papers in
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- Numerical methods for differential equations 4
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- Magnetic Bearings and Levitation Dynamics 1
- Co-authors
- Daniele Mortari (12 shared papers)Carl Leake (6 shared papers)Roberto Furfaro (3 shared papers)Enrico Schiassi (3 shared papers)Mario De Florio (1 shared paper)Kristofer Drozd (1 shared paper)Martin W. Lo (1 shared paper)Yalchin Efendiev (1 shared paper)
- Journals
- Journal of Computational and Applied Mathematics (2 papers)Neurocomputing (1 paper)Acta Astronautica (1 paper)Advances in Space Research (1 paper)Mathematics (3 papers)
- Partner nations
- United StatesBrazil
In The Last Decade
Hunter Johnston
13 papers receiving 300 citations
Peers
Comparison fields: 5 of 40
- Statistical and Nonlinear Physics 145
- Numerical Analysis 62
- Modeling and Simulation 47
- Statistics, Probability and Uncertainty 33
- Aerospace Engineering 96
Countries citing papers authored by Hunter Johnston
This map shows the geographic impact of Hunter Johnston'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 Hunter Johnston with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hunter Johnston more than expected).
Fields of papers citing papers by Hunter Johnston
This network shows the impact of papers produced by Hunter Johnston. 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 Hunter Johnston. The network helps show where Hunter Johnston may publish in the future.
Co-authors
The 12 scholars most cited alongside Hunter Johnston, 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 | 2021 | 128 | |
| 2 | 2018 | 53 | |
| 3 | 2020 | 33 | |
| 4 | 2021 | 23 | |
| 5 | 2019 | 17 | |
| 6 | 2021 | 16 | |
| 7 | 2021 | 13 | |
| 8 | 2019 | 10 | |
| 9 | 2021 | 10 | |
| 10 | 2022 | 5 | |
| 11 | 2018 | 2 | |
| 12 | Theory of Connections Applied to Support Vector Machines to Solve Differential Equations. | 2018 | 1 |
| 13 | 2017 | 1 |
About Hunter Johnston
Hunter Johnston is a scholar working on Numerical Analysis, Control and Systems Engineering, Statistical and Nonlinear Physics, Astronomy and Astrophysics and Aerospace Engineering, having authored 13 papers that have together received 312 indexed citations. Recurring topics across this work include Numerical methods for differential equations (4 papers), Model Reduction and Neural Networks (4 papers), Spacecraft Dynamics and Control (3 papers), Stellar, planetary, and galactic studies (2 papers), Probabilistic and Robust Engineering Design (2 papers), Aerospace Engineering and Control Systems (1 paper), Magnetic Bearings and Levitation Dynamics (1 paper) and Pulsars and Gravitational Waves Research (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (145 citations), Numerical Analysis (62 citations), Modeling and Simulation (47 citations), Statistics, Probability and Uncertainty (33 citations) and Aerospace Engineering (96 citations). Hunter Johnston has collaborated with scholars based in United States and Brazil. Frequent co-authors include Daniele Mortari, Carl Leake, Roberto Furfaro, Enrico Schiassi, Mario De Florio, Kristofer Drozd, Martin W. Lo, Yalchin Efendiev, Andrea D’Ambrosio and Fabio Curti. Their work appears in journals such as Journal of Computational and Applied Mathematics, Neurocomputing, Acta Astronautica, Advances in Space Research and Mathematics.
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.