David Pearson
- Artificial Intelligence top 5%
- Quantum Information and Cryptography 5
- Quantum Computing Algorithms and Architecture 4
- Computational Mechanics top 5%
- Fluid Dynamics and Turbulent Flows 2
- Sparse and Compressive Sensing Techniques 1
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- Model Reduction and Neural Networks 2
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- Adaptive optics and wavefront sensing 1
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- Wind and Air Flow Studies 2
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- Advanced Optical Sensing Technologies 1
- Co-authors
- Paul J. GoulartBharathram GanapathisubramaniChip ElliottAndrew WynnGregory D. TroxelJ. SchlaferTai Tsun WuJohn M. Myers
- Journals
- Journal of Fluid Mechanics (2 papers)Journal of Physics Conference Series (1 paper)AIP conference proceedings (1 paper)
- Partner nations
- United KingdomSwitzerlandUnited States
In The Last Decade
David Pearson
9 papers receiving 501 citations
Peers
Comparison fields: 5 of 43
- Artificial Intelligence 288
- Computational Mechanics 177
- Statistical and Nonlinear Physics 87
- Atomic and Molecular Physics, and Optics 215
- Environmental Engineering 65
Countries citing papers authored by David Pearson
This map shows the geographic impact of David Pearson'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 David Pearson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Pearson more than expected).
Fields of papers citing papers by David Pearson
This network shows the impact of papers produced by David Pearson. 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 David Pearson. The network helps show where David Pearson may publish in the future.
Co-authorship network
The 13 scholars most cited alongside David Pearson, 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 | 2013 | 87 | |
| 2 | 2013 | 123 | |
| 3 | 2012 | 15 | |
| 4 | 2011 | 8 | |
| 5 | 2006 | 1 | |
| 6 | 2005 | 164 | |
| 7 | 2004 | 2 | |
| 8 | 2004 | 43 | |
| 9 | 2003 | 85 |
About David Pearson
David Pearson is a scholar working on Instrumentation, Computational Mechanics, Statistical and Nonlinear Physics, Artificial Intelligence and Environmental Engineering, having authored 9 papers that have together received 528 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (5 papers), Quantum Computing Algorithms and Architecture (4 papers), Fluid Dynamics and Turbulent Flows (2 papers), Wind and Air Flow Studies (2 papers), Model Reduction and Neural Networks (2 papers), Adaptive optics and wavefront sensing (1 paper), Sparse and Compressive Sensing Techniques (1 paper) and Advanced Optical Sensing Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (288 citations), Computational Mechanics (177 citations), Statistical and Nonlinear Physics (87 citations), Atomic and Molecular Physics, and Optics (215 citations) and Environmental Engineering (65 citations). David Pearson has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Paul J. Goulart, Bharathram Ganapathisubramani, Chip Elliott, Andrew Wynn, Gregory D. Troxel, J. Schlafer, Tai Tsun Wu, John M. Myers, R. E. Schwall and Jonathan L. Habif. Their work appears in journals such as Journal of Fluid Mechanics, Journal of Physics Conference Series, AIP conference proceedings and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.