Timon Rabczuk

636 total citations · 2 hit papers
14 papers, 396 citations indexed

About

Timon Rabczuk is a scholar working on Statistical and Nonlinear Physics, Mechanics of Materials and Computational Mechanics. According to data from OpenAlex, Timon Rabczuk has authored 14 papers receiving a total of 396 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Statistical and Nonlinear Physics, 5 papers in Mechanics of Materials and 5 papers in Computational Mechanics. Recurrent topics in Timon Rabczuk's work include Numerical methods in engineering (5 papers), Model Reduction and Neural Networks (5 papers) and Advanced Numerical Analysis Techniques (4 papers). Timon Rabczuk is often cited by papers focused on Numerical methods in engineering (5 papers), Model Reduction and Neural Networks (5 papers) and Advanced Numerical Analysis Techniques (4 papers). Timon Rabczuk collaborates with scholars based in Germany, China and Australia. Timon Rabczuk's co-authors include Stéphane Bordas, Pierre Kerfriden, Cosmin Anitescu, Olivier Goury, Yizheng Wang, Mohammad Sadegh Eshaghi, Xiaoying Zhuang, Somdatta Goswami, Vinh Phu Nguyen and Yinghua Liu and has published in prestigious journals such as International Journal of Heat and Mass Transfer, Computer Methods in Applied Mechanics and Engineering and Neurocomputing.

In The Last Decade

Timon Rabczuk

14 papers receiving 370 citations

Hit Papers

2 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Kolmogorov–Arnold-Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov–Arnold Networks

2024 53 citations Yizheng Wang, Jinshuai Bai et al. Computer Methods in Applied Mechanics and Engineering profile →
Variational Physics-informed Neural Operator (VINO) for solving partial differential equations

2025 34 citations Mohammad Sadegh Eshaghi, Cosmin Anitescu et al. Computer Methods in Applied Mechanics and Engineering profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Timon Rabczuk Germany	11	175	124	103	89	55	14	396
Étienne Pruliére France	11	142 0.8×	78 0.6×	123 1.2×	51 0.6×	39 0.7×	17	308
Chensen Ding China	14	145 0.8×	164 1.3×	73 0.7×	93 1.0×	47 0.9×	27	398
Robert Eggersmann Germany	5	205 1.2×	48 0.4×	148 1.4×	79 0.9×	67 1.2×	7	369
Jakob T. Ostien United States	10	190 1.1×	144 1.2×	35 0.3×	78 0.9×	71 1.3×	15	344
Konstantinos Agathos Switzerland	14	472 2.7×	227 1.8×	56 0.5×	209 2.3×	90 1.6×	26	602
Francisco Chinesta France	10	154 0.9×	131 1.1×	146 1.4×	40 0.4×	92 1.7×	27	399
Anindya Bhaduri United States	8	144 0.8×	31 0.3×	62 0.6×	76 0.9×	93 1.7×	23	300
Bahador Bahmani United States	12	161 0.9×	37 0.3×	65 0.6×	52 0.6×	50 0.9×	20	298
Diego Hayashi Alonso Brazil	11	51 0.3×	144 1.2×	121 1.2×	128 1.4×	95 1.7×	24	334
I. Alfaro Spain	6	146 0.8×	144 1.2×	220 2.1×	62 0.7×	81 1.5×	7	475

Countries citing papers authored by Timon Rabczuk

Since Specialization

Citations

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

Fields of papers citing papers by Timon Rabczuk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Timon Rabczuk

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

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

Eshaghi, Mohammad Sadegh, et al.. (2025). Variational Physics-informed Neural Operator (VINO) for solving partial differential equations. Computer Methods in Applied Mechanics and Engineering. 437. 117785–117785. 34 indexed citations breakdown →

Dias, Daniel, et al.. (2025). Physics-informed neural network for elastic–plastic mesh-free modelling of tunnelling-induced deformation. Acta Geotechnica. 21(1). 349–370. 1 indexed citations

Wang, Yizheng, Jinshuai Bai, Mohammad Sadegh Eshaghi, et al.. (2025). Transfer Learning in Physics‐Informed Neurals Networks: Full Fine‐Tuning, Lightweight Fine‐Tuning, and Low‐Rank Adaptation. 5(2). 212–235. 9 indexed citations

Wang, Yizheng, Jinshuai Bai, Cosmin Anitescu, et al.. (2024). Kolmogorov–Arnold-Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov–Arnold Networks. Computer Methods in Applied Mechanics and Engineering. 433. 117518–117518. 53 indexed citations breakdown →

Gao, Jie, et al.. (2024). Multi-objective topology optimization for solid-porous infill designs in regions-divided structures using multi-patch isogeometric analysis. Computer Methods in Applied Mechanics and Engineering. 428. 117095–117095. 22 indexed citations

Eshaghi, Mohammad Sadegh, et al.. (2024). Applications of scientific machine learning for the analysis of functionally graded porous beams. Neurocomputing. 619. 129119–129119. 14 indexed citations

Ren, Huilong, Xiaoying Zhuang, Hehua Zhu, & Timon Rabczuk. (2024). Variational damage model: A novel consistent approach to fracture. Computers & Structures. 305. 107518–107518. 21 indexed citations

Goswami, Somdatta, et al.. (2021). A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation. arXiv (Cornell University). 50 indexed citations

Xu, Gang, et al.. (2018). Exact conversion from Bézier tetrahedra to Bézier hexahedra. Computer Aided Geometric Design. 62. 154–165. 5 indexed citations

10.

Rabczuk, Timon, et al.. (2018). Mathematical and computational modeling of drug release from an ocular iontophoretic drug delivery device. International Journal of Heat and Mass Transfer. 123. 1035–1049. 14 indexed citations

11.

Ferreira, J.A., et al.. (2016). Tuning polymeric and drug properties in a drug eluting stent: A numerical study. Applied Mathematical Modelling. 40(17-18). 8067–8086. 10 indexed citations

12.

Nguyen, Vinh Phu, Pierre Kerfriden, Stéphane Bordas, & Timon Rabczuk. (2014). Isogeometric analysis suitable trivariate NURBS representation of composite panels with a new offset algorithm. Computer-Aided Design. 55. 49–63. 32 indexed citations

13.

Kerfriden, Pierre, Olivier Goury, Timon Rabczuk, & Stéphane Bordas. (2012). A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics. Computer Methods in Applied Mechanics and Engineering. 256. 169–188. 110 indexed citations

14.

Bordas, Stéphane, et al.. (2010). Recent Advances Towards Reducing the Meshing and Re-Meshing Burden in Computational Sciences. ORCA Online Research @Cardiff (Cardiff University). 2. 51–82. 21 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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