Boris Krämer
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- Probabilistic and Robust Engineering Design 22
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- Model Reduction and Neural Networks 32
- Numerical Analysis top 5%
- Numerical methods for differential equations 11
- Mechanical Engineering top 5%
- Teleoperation and Haptic Systems 7
- Computational Mechanics top 5%
- Fluid Dynamics and Turbulent Flows 7
- Fluid Dynamics and Vibration Analysis 6
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- Structural Health Monitoring Techniques 5
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- Nuclear reactor physics and engineering 5
- Co-authors
- Karen WillcoxB. F. von TurkovichBenjamin PeherstorferNam P. SuhElizabeth QianH. KazerooniZhu WangMouhacine Benosman
- Journals
- Computer Methods in Applied Mechanics and Engineering (8 papers)Journal of Computational Physics (5 papers)SIAM/ASA Journal on Uncertainty Quantification (4 papers)
- Partner nations
- United StatesJapanGermany
In The Last Decade
Boris Krämer
67 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 93
- Statistics, Probability and Uncertainty 331
- Statistical and Nonlinear Physics 496
- Numerical Analysis 116
- Mechanical Engineering 687
- Computational Mechanics 246
Countries citing papers authored by Boris Krämer
This map shows the geographic impact of Boris Krämer'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 Boris Krämer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Boris Krämer more than expected).
Fields of papers citing papers by Boris Krämer
This network shows the impact of papers produced by Boris Krämer. 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 Boris Krämer. The network helps show where Boris Krämer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Boris Krämer, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 11 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 7 | |
| 8 | 2024 | 3 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 0 | |
| 11 | 2024 | 1 | |
| 12 | 2023 | 18 | |
| 13 | 2023 | 3 | |
| 14 | 2023 | 9 | |
| 15 | 2023 | 15 | |
| 16 | 2022 | 48 | |
| 17 | 2019 | 21 | |
| 18 | Sparse Sensing and DMD-Based Identification of Flow Regimes and Bifurcations in Complex Flows | 2017 | 2 |
| 19 | 1987 | 93 | |
| 20 | Development Agreements: To What Extent Are They Enforceable? | 1981 | 1 |
About Boris Krämer
Boris Krämer is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Numerical Analysis, having authored 77 papers that have together received 1.6k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (32 papers), Probabilistic and Robust Engineering Design (22 papers), Numerical methods for differential equations (11 papers), Fluid Dynamics and Turbulent Flows (7 papers), Teleoperation and Haptic Systems (7 papers), Fluid Dynamics and Vibration Analysis (6 papers), Structural Health Monitoring Techniques (5 papers) and Nuclear reactor physics and engineering (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (331 citations), Statistical and Nonlinear Physics (496 citations) and Numerical Analysis (116 citations). Boris Krämer has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Karen Willcox, B. F. von Turkovich, Benjamin Peherstorfer, Nam P. Suh, Elizabeth Qian, H. Kazerooni, Zhu Wang, Mouhacine Benosman, Padmini Rangamani and Serkan Gugercin. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Journal of Computational Physics, SIAM/ASA Journal on Uncertainty Quantification, SIAM Journal on Applied Dynamical Systems and CIRP Annals.
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.