John R. Singler
Impact in
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- Model Reduction and Neural Networks
- Numerical Analysis top 5%
- Numerical methods for differential equations
Papers in
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- Model Reduction and Neural Networks 35
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- Probabilistic and Robust Engineering Design 17
- Co-authors
- Yangwen ZhangS. JagannathanBenjamin T. DickinsonWeiwei HuDouglas A. BristowEhsan ArabiTansel YucelenMariano Mateos
- Journals
- SIAM Journal on Numerical Analysis (4 papers)Journal of Computational and Applied Mathematics (4 papers)IEEE Transactions on Neural Networks and Learning Systems (3 papers)Journal of Mathematical Analysis and Applications (3 papers)Numerische Mathematik (2 papers)
- Partner nations
- United StatesChinaSpain
In The Last Decade
John R. Singler
63 papers receiving 515 citations
Peers
Comparison fields: 5 of 49
- Statistical and Nonlinear Physics 278
- Numerical Analysis 107
- Statistics, Probability and Uncertainty 105
- Computational Mechanics 230
- Control and Systems Engineering 155
Countries citing papers authored by John R. Singler
This map shows the geographic impact of John R. Singler'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 John R. Singler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John R. Singler more than expected).
Fields of papers citing papers by John R. Singler
This network shows the impact of papers produced by John R. Singler. 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 John R. Singler. The network helps show where John R. Singler may publish in the future.
Co-authors
The 24 scholars most cited alongside John R. Singler, 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 | 2024 | 2 | |
| 2 | 2023 | 3 | |
| 3 | 2023 | 7 | |
| 4 | 2022 | 1 | |
| 5 | 2022 | 5 | |
| 6 | 2021 | 0 | |
| 7 | 2020 | 21 | |
| 8 | 2020 | 16 | |
| 9 | 2020 | 5 | |
| 10 | An Optimal EDG Method for Distributed Control of Convection Diffusion PDEs | 2019 | 3 |
| 11 | A new HDG method for Dirichlet boundary control of convection diffusion PDEs II: Low regularity | 2018 | 21 |
| 12 | 2018 | 24 | |
| 13 | 2017 | 28 | |
| 14 | 2014 | 3 | |
| 15 | 2011 | 13 | |
| 16 | Nonlinear Model Reduction Using Group Proper Orthogonal Decomposition | 2010 | 12 |
| 17 | 2008 | 15 | |
| 18 | 2007 | 1 | |
| 19 | 2007 | 3 | |
| 20 | 2006 | 9 |
About John R. Singler
John R. Singler is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty, Numerical Analysis, Computational Mechanics and Control and Systems Engineering, having authored 64 papers that have together received 533 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (35 papers), Probabilistic and Robust Engineering Design (17 papers), Advanced Numerical Methods in Computational Mathematics (13 papers), Numerical methods for differential equations (11 papers), Stability and Controllability of Differential Equations (10 papers), Fluid Dynamics and Turbulent Flows (8 papers), Computational Fluid Dynamics and Aerodynamics (8 papers) and Advanced Mathematical Modeling in Engineering (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (278 citations), Numerical Analysis (107 citations), Statistics, Probability and Uncertainty (105 citations), Computational Mechanics (230 citations) and Control and Systems Engineering (155 citations). John R. Singler has collaborated with scholars based in United States, China and Spain. Frequent co-authors include Yangwen Zhang, S. Jagannathan, Benjamin T. Dickinson, Weiwei Hu, Douglas A. Bristow, Ehsan Arabi, Tansel Yucelen, Mariano Mateos, Wei Gong and Xiaobo Zheng. Their work appears in journals such as SIAM Journal on Numerical Analysis, Journal of Computational and Applied Mathematics, IEEE Transactions on Neural Networks and Learning Systems, Journal of Mathematical Analysis and Applications and Numerische Mathematik.
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.