Jonas Kusch

419 total citations
27 papers, 230 citations indexed

About

Jonas Kusch is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Jonas Kusch has authored 27 papers receiving a total of 230 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Mechanics, 12 papers in Statistical and Nonlinear Physics and 8 papers in Statistics, Probability and Uncertainty. Recurrent topics in Jonas Kusch's work include Model Reduction and Neural Networks (12 papers), Probabilistic and Robust Engineering Design (8 papers) and Advanced Numerical Methods in Computational Mathematics (7 papers). Jonas Kusch is often cited by papers focused on Model Reduction and Neural Networks (12 papers), Probabilistic and Robust Engineering Design (8 papers) and Advanced Numerical Methods in Computational Mathematics (7 papers). Jonas Kusch collaborates with scholars based in Germany, Austria and Norway. Jonas Kusch's co-authors include Christian Lubich, Martin Frank, Lukas Einkemmer, Ryan G. McClarren, Christian Klingenberg, Katharina Kormann, Christos Reppas, M. J. Frank, Cordula Stillhart and Werner Weitschies and has published in prestigious journals such as Journal of Computational Physics, SIAM Journal on Numerical Analysis and SIAM Journal on Scientific Computing.

In The Last Decade

Jonas Kusch

24 papers receiving 203 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonas Kusch Germany 10 121 110 49 44 38 27 230
Viêt Hà Hòang Singapore 11 56 0.5× 202 1.8× 12 0.2× 125 2.8× 198 5.2× 43 371
Axel Kröner France 7 36 0.3× 122 1.1× 4 0.1× 11 0.3× 96 2.5× 21 215
Tyrone Rees United Kingdom 8 28 0.2× 290 2.6× 8 0.2× 23 0.5× 321 8.4× 18 411
Petr Tichý Czechia 9 27 0.2× 135 1.2× 11 0.2× 3 0.1× 209 5.5× 26 294
Jean-Paul Calvi France 11 33 0.3× 141 1.3× 3 0.1× 35 0.8× 97 2.6× 26 336
G. Scherer United Kingdom 6 14 0.1× 46 0.4× 8 0.2× 5 0.1× 22 0.6× 11 105
Jianbo Cui China 10 28 0.2× 66 0.6× 24 0.5× 91 2.4× 31 288
Peter Brune United States 5 23 0.2× 84 0.8× 2 0.0× 4 0.1× 55 1.4× 7 201
C. S. Ryoo South Korea 13 113 0.9× 54 0.5× 23 0.5× 59 1.6× 152 615
Yuto Miyatake Japan 9 82 0.7× 73 0.7× 10 0.2× 66 1.7× 39 235

Countries citing papers authored by Jonas Kusch

Since Specialization
Citations

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

Fields of papers citing papers by Jonas Kusch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonas Kusch

This figure shows the co-authorship network connecting the top 25 collaborators of Jonas Kusch. A scholar is included among the top collaborators of Jonas Kusch 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 Jonas Kusch. Jonas Kusch 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.
Kusch, Jonas, et al.. (2026). A Parallel, Energy-Stable Low-Rank Integrator for Nonlinear Multi-Scale Thermal Radiative Transfer. Journal of Computational and Theoretical Transport. 1–45.
2.
Frank, M. J., et al.. (2025). Asymptotic-Preserving and Energy Stable Dynamical Low-Rank Approximation for Thermal Radiative Transfer Equations. Multiscale Modeling and Simulation. 23(1). 278–312. 2 indexed citations
3.
Einkemmer, Lukas, Katharina Kormann, Jonas Kusch, Ryan G. McClarren, & Jing‐Mei Qiu. (2025). A review of low-rank methods for time-dependent kinetic simulations. Journal of Computational Physics. 538. 114191–114191. 4 indexed citations
4.
Einkemmer, Lukas, et al.. (2025). A Multi-fidelity Adaptive Dynamical Low-Rank Based Optimization Algorithm for Fission Criticality Problems. Journal of Scientific Computing. 104(1). 1 indexed citations
5.
6.
Einkemmer, Lukas, et al.. (2024). A robust second-order low-rank BUG integrator based on the midpoint rule. BIT Numerical Mathematics. 64(3). 9 indexed citations
7.
Kusch, Jonas, et al.. (2024). A Parallel Rank-Adaptive Integrator for Dynamical Low-Rank Approximation. SIAM Journal on Scientific Computing. 46(3). B205–B228. 11 indexed citations
8.
Einkemmer, Lukas, Katharina Kormann, Jonas Kusch, Ryan G. McClarren, & Jing‐Mei Qiu. (2024). A review of low-rank methods for time-dependent kinetic simulations. arXiv (Cornell University).
9.
Kusch, Jonas, et al.. (2023). A Flux Reconstruction Stochastic Galerkin Scheme for Hyperbolic Conservation Laws. Journal of Scientific Computing. 95(1). 1 indexed citations
10.
Stillhart, Cordula, Jonas Kusch, Patrick Augustijns, et al.. (2023). The impact of advanced age on gastrointestinal characteristics that are relevant to oral drug absorption: An AGePOP review. European Journal of Pharmaceutical Sciences. 187. 106452–106452. 17 indexed citations
11.
Kusch, Jonas, et al.. (2023). On the Stability of Robust Dynamical Low-Rank Approximations for Hyperbolic Problems. SIAM Journal on Scientific Computing. 45(1). A1–A24. 12 indexed citations
12.
Kusch, Jonas, et al.. (2023). KiT-RT: An Extendable Framework for Radiative Transfer and Therapy. ACM Transactions on Mathematical Software. 49(4). 1–24. 2 indexed citations
13.
Frank, Martin, et al.. (2022). A realizable filtered intrusive polynomial moment method. Journal of Computational and Applied Mathematics. 407. 114055–114055. 1 indexed citations
14.
Kusch, Jonas, et al.. (2022). A rank-adaptive robust integrator for dynamical low-rank approximation. BIT Numerical Mathematics. 62(4). 1149–1174. 53 indexed citations
15.
Kusch, Jonas, et al.. (2022). DYNAMICAL LOW-RANK APPROXIMATION FOR BURGERS' EQUATION WITH UNCERTAINTY. International Journal for Uncertainty Quantification. 12(5). 1–21. 15 indexed citations
16.
Kusch, Jonas. (2020). Realizability-preserving discretization strategies for hyperbolic and kinetic equations with uncertainty. Repository KITopen (Karlsruhe Institute of Technology). 2 indexed citations
17.
Kusch, Jonas, et al.. (2020). Intrusive acceleration strategies for uncertainty quantification for hyperbolic systems of conservation laws. Journal of Computational Physics. 419. 109698–109698. 8 indexed citations
18.
Frank, Martin, et al.. (2019). Highly uniform quadrature sets for the discrete ordinates method. 449. 1 indexed citations
19.
Frank, Martin, et al.. (2019). Ray effect mitigation for the discrete ordinates method through quadrature rotation. Journal of Computational Physics. 382. 105–123. 15 indexed citations
20.
Kusch, Jonas & Martin Frank. (2019). An adaptive quadrature-based moment closure. International Journal of Advances in Engineering Sciences and Applied Mathematics. 11(3). 174–186. 1 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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