Kevin Carlberg
- Statistical and Nonlinear Physics top 0.5%
- Computational Mechanics top 1%
- Statistics, Probability and Uncertainty top 0.2%
- Numerical Analysis top 2%
- Aerospace Engineering top 5%
- Co-authors
- Charbel FarhatDavid AmsallemJulien CortialCharbel Bou‐MoslehYoungsoo ChoiLouis J. DurlofskyEric ParishRay Tuminaro
- Topics
- Model Reduction and Neural Networks (33 papers)Probabilistic and Robust Engineering Design (18 papers)Fluid Dynamics and Vibration Analysis (8 papers)
- Journals
- Journal of Computational PhysicsComputer Methods in Applied Mechanics and EngineeringAIAA Journal
- Partner nations
- United StatesCanadaRussia
In The Last Decade
Kevin Carlberg
33 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 68
- Statistical and Nonlinear Physics 1.5k
- Computational Mechanics 850
- Statistics, Probability and Uncertainty 656
- Numerical Analysis 240
- Aerospace Engineering 207
Countries citing papers authored by Kevin Carlberg
This map shows the geographic impact of Kevin Carlberg'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 Kevin Carlberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Carlberg more than expected).
Fields of papers citing papers by Kevin Carlberg
This network shows the impact of papers produced by Kevin Carlberg. 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 Kevin Carlberg. The network helps show where Kevin Carlberg may publish in the future.
Co-authorship network of co-authors of Kevin Carlberg
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Carlberg. A scholar is included among the top collaborators of Kevin Carlberg 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 Kevin Carlberg. Kevin Carlberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 6 | |
| 3 | 2 | |
| 4 | 19 | |
| 5 | 24 | |
| 6 | 10 | |
| 7 | 19 | |
| 8 | 25 | |
| 9 | Online adaptive basis refinement and compression for reduced-order models. | 2 |
| 10 | 51 | |
| 11 | Error estimation for surrogate models of dynamical systems using machine learning. | 4 |
| 12 | 47 | |
| 13 | 17 | |
| 14 | 11 | |
| 15 | 88 | |
| 16 | 9 | |
| 17 | 20 | |
| 18 | 80 | |
| 19 | 1 | |
| 20 | 176 |
About Kevin Carlberg
Kevin Carlberg is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 33 papers that have together received 1.7k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (33 papers), Probabilistic and Robust Engineering Design (18 papers) and Fluid Dynamics and Vibration Analysis (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.5k citations), Statistics, Probability and Uncertainty (656 citations) and Numerical Analysis (240 citations). Kevin Carlberg has collaborated with scholars based in United States, Canada and Russia. Frequent co-authors include Charbel Farhat, David Amsallem, Julien Cortial, Charbel Bou‐Mosleh, Youngsoo Choi, Louis J. Durlofsky, Eric Parish, Ray Tuminaro, Francesco Rizzi and Freddie Witherden. Their work appears in journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and AIAA Journal.
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.