Philipp Bekemeyer

591 total citations
49 papers, 386 citations indexed

About

Philipp Bekemeyer is a scholar working on Statistics, Probability and Uncertainty, Computational Mechanics and Statistical and Nonlinear Physics. According to data from OpenAlex, Philipp Bekemeyer has authored 49 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Statistics, Probability and Uncertainty, 27 papers in Computational Mechanics and 26 papers in Statistical and Nonlinear Physics. Recurrent topics in Philipp Bekemeyer's work include Probabilistic and Robust Engineering Design (28 papers), Model Reduction and Neural Networks (26 papers) and Computational Fluid Dynamics and Aerodynamics (22 papers). Philipp Bekemeyer is often cited by papers focused on Probabilistic and Robust Engineering Design (28 papers), Model Reduction and Neural Networks (26 papers) and Computational Fluid Dynamics and Aerodynamics (22 papers). Philipp Bekemeyer collaborates with scholars based in Germany, United Kingdom and United States. Philipp Bekemeyer's co-authors include Sebastian Timme, Stefan Görtz, Ralf Heinrich, Stefan Langer, Carsten M. Liersch, Nils Hoffmann, Robert Hoppe, Markus Widhalm, Sanjiv Sharma and Jan Delfs and has published in prestigious journals such as AIAA Journal, Physics of Fluids and Energies.

In The Last Decade

Philipp Bekemeyer

41 papers receiving 368 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Philipp Bekemeyer Germany 13 232 186 152 122 37 49 386
Mathieu Couplet France 8 216 0.9× 245 1.3× 119 0.8× 213 1.7× 54 1.5× 13 492
Marcus Meyer Germany 11 228 1.0× 126 0.7× 211 1.4× 162 1.3× 81 2.2× 70 505
Nicola Demo Italy 11 118 0.5× 207 1.1× 71 0.5× 80 0.7× 24 0.6× 22 336
Elizabeth A. Lurie United States 5 477 2.1× 97 0.5× 206 1.4× 47 0.4× 21 0.6× 8 579
Elizabeth Qian United States 7 108 0.5× 215 1.2× 96 0.6× 98 0.8× 18 0.5× 10 378
Malik Hassanaly United States 14 287 1.2× 74 0.4× 81 0.5× 34 0.3× 12 0.3× 39 430
Emiliano Iuliano Italy 11 139 0.6× 82 0.4× 158 1.0× 91 0.7× 88 2.4× 23 334
C. B. Allen United Kingdom 11 544 2.3× 114 0.6× 238 1.6× 110 0.9× 111 3.0× 13 680
Vamshi Korivi United States 17 464 2.0× 102 0.5× 121 0.8× 138 1.1× 39 1.1× 44 621

Countries citing papers authored by Philipp Bekemeyer

Since Specialization
Citations

This map shows the geographic impact of Philipp Bekemeyer'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 Philipp Bekemeyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Bekemeyer more than expected).

Fields of papers citing papers by Philipp Bekemeyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philipp Bekemeyer. 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 Philipp Bekemeyer. The network helps show where Philipp Bekemeyer may publish in the future.

Co-authorship network of co-authors of Philipp Bekemeyer

This figure shows the co-authorship network connecting the top 25 collaborators of Philipp Bekemeyer. A scholar is included among the top collaborators of Philipp Bekemeyer 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 Philipp Bekemeyer. Philipp Bekemeyer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bekemeyer, Philipp, et al.. (2025). Predicting onflow parameters using transfer learning for domain and task adaptation. Aerospace Science and Technology. 168. 111161–111161.
2.
Bekemeyer, Philipp, et al.. (2025). Nonlinear Unsteady Aerodynamic Reduced-Order Modeling Using a Surrogate-Based Recurrent Framework. Journal of Aircraft. 62(6). 1560–1574.
3.
Langer, Stefan, et al.. (2025). Physics-informed neural networks for inviscid transonic flows around an airfoil. Physics of Fluids. 37(8). 2 indexed citations
4.
Bekemeyer, Philipp, et al.. (2025). Introduction of Applied Aerodynamics Surrogate Modeling Benchmark Cases. elib (German Aerospace Center). 1 indexed citations
5.
Langer, Stefan, et al.. (2025). Adopting Computational Fluid Dynamics Concepts for Physics-Informed Neural Networks. elib (German Aerospace Center).
6.
Bekemeyer, Philipp, et al.. (2024). Surrogate based design space exploration and exploitation for an efficient airfoil optimization under uncertainties using transition models. Aerospace Science and Technology. 154. 109532–109532. 2 indexed citations
7.
Langer, Stefan, et al.. (2024). Solving transport equations on quantum computers—potential and limitations of physics-informed quantum circuits. CEAS Aeronautical Journal. 16(1). 63–80. 4 indexed citations
8.
Bekemeyer, Philipp, et al.. (2024). Sensor placement for optimal aerodynamic data fusion. Aerospace Science and Technology. 155. 109598–109598. 4 indexed citations
9.
Bekemeyer, Philipp, et al.. (2024). Multi-Fidelity Adaptive Sampling for Surrogate-Based Optimization and Uncertainty Quantification. Aerospace. 11(6). 448–448. 4 indexed citations
10.
Bekemeyer, Philipp, et al.. (2024). Nonlinear Unsteady Aerodynamic Reduced-Order Modeling Using a Surrogate-Based Recurrent Framework. elib (German Aerospace Center).
11.
Bekemeyer, Philipp, et al.. (2023). Adjoint high-dimensional aircraft shape optimization using a CAD-ROM parameterization. CEAS Aeronautical Journal. 14(3). 729–738. 2 indexed citations
12.
Bekemeyer, Philipp, et al.. (2023). Unsteady reduced order model with neural networks and flight-physics-based regularization for aerodynamic applications. Computers & Fluids. 264. 105949–105949. 15 indexed citations
13.
Bekemeyer, Philipp, et al.. (2023). Graph neural networks for the prediction of aircraft surface pressure distributions. Aerospace Science and Technology. 137. 108268–108268. 34 indexed citations
14.
Bekemeyer, Philipp, et al.. (2023). PHYSICS-BASED REGULARIZATION OF NEURAL NETWORKS FOR AERODYNAMIC FLOW PREDICTIONS. elib (German Aerospace Center). 22–39. 1 indexed citations
15.
16.
Bekemeyer, Philipp, et al.. (2022). Unsteady physics-based reduced order modeling for large-scale compressible aerodynamic applications. Computers & Fluids. 239. 105385–105385. 11 indexed citations
17.
Bekemeyer, Philipp, et al.. (2022). Data-Driven Aerodynamic Modeling Using the DLR SMARTy Toolbox. AIAA AVIATION 2022 Forum. 23 indexed citations
18.
Bekemeyer, Philipp, et al.. (2022). High-fidelity Aerodynamic and Aeroacoustic Multi-Objective Bayesian Optimization. AIAA AVIATION 2022 Forum. 5 indexed citations
19.
Liersch, Carsten M., et al.. (2020). An aerodynamic variable-fidelity modelling framework for a low-observable UCAV. Aerospace Science and Technology. 107. 106232–106232. 15 indexed citations
20.
Bekemeyer, Philipp & Sebastian Timme. (2019). Flexible aircraft gust encounter simulation using subspace projection model reduction. Aerospace Science and Technology. 86. 805–817. 22 indexed citations

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.

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