David Amsallem
- Statistical and Nonlinear Physics top 0.2%
- Computational Mechanics top 0.5%
- Statistics, Probability and Uncertainty top 0.1%
- Civil and Structural Engineering top 5%
- Numerical Analysis top 2%
- Co-authors
- Charbel FarhatJulien CortialMatthew J. ZahrKevin CarlbergAndrea ManzoniFederico NegriYoungsoo ChoiBernard Haasdonk
- Topics
- Model Reduction and Neural Networks (33 papers)Probabilistic and Robust Engineering Design (19 papers)Computational Fluid Dynamics and Aerodynamics (10 papers)
- Journals
- Journal of Computational PhysicsAIAA JournalInternational Journal for Numerical Methods in Engineering
- Partner nations
- United StatesSwedenSwitzerland
In The Last Decade
David Amsallem
35 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Statistical and Nonlinear Physics 2.1k
- Computational Mechanics 1.2k
- Statistics, Probability and Uncertainty 1.1k
- Civil and Structural Engineering 358
- Numerical Analysis 355
Countries citing papers authored by David Amsallem
This map shows the geographic impact of David Amsallem'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 Amsallem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Amsallem more than expected).
Fields of papers citing papers by David Amsallem
This network shows the impact of papers produced by David Amsallem. 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 Amsallem. The network helps show where David Amsallem may publish in the future.
Co-authorship network of co-authors of David Amsallem
This figure shows the co-authorship network connecting the top 25 collaborators of David Amsallem. A scholar is included among the top collaborators of David Amsallem 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 David Amsallem. David Amsallem is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 49 | |
| 2 | 9 | |
| 3 | 7 | |
| 4 | 61 | |
| 5 | 38 | |
| 6 | 92 | |
| 7 | 112 | |
| 8 | 104 | |
| 9 | 18 | |
| 10 | 42 | |
| 11 | 8 | |
| 12 | 144 | |
| 13 | 9 | |
| 14 | 1 | |
| 15 | 20 | |
| 16 | 1 | |
| 17 | 176 | |
| 18 | 14 | |
| 19 | Interpolation Method for Adapting Reduced-Order Models and Application to Aeroelasticitybreakdown → | 492 |
| 20 | 13 |
About David Amsallem
David Amsallem is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 35 papers that have together received 2.7k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (33 papers), Probabilistic and Robust Engineering Design (19 papers) and Computational Fluid Dynamics and Aerodynamics (10 papers). The work is most often cited by research in Statistical and Nonlinear Physics (2.1k citations), Statistics, Probability and Uncertainty (1.1k citations) and Numerical Analysis (355 citations). David Amsallem has collaborated with scholars based in United States, Sweden and Switzerland. Frequent co-authors include Charbel Farhat, Julien Cortial, Matthew J. Zahr, Kevin Carlberg, Andrea Manzoni, Federico Negri, Youngsoo Choi, Bernard Haasdonk, Ulrich Hetmaniuk and Rémi Abgrall. Their work appears in journals such as Journal of Computational Physics, AIAA Journal and International Journal for Numerical Methods in Engineering.
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.