Moritz Flaschel

996 total citations · 2 hit papers
17 papers, 634 citations indexed

About

Moritz Flaschel is a scholar working on Biomedical Engineering, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Moritz Flaschel has authored 17 papers receiving a total of 634 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Biomedical Engineering, 8 papers in Statistical and Nonlinear Physics and 7 papers in Statistics, Probability and Uncertainty. Recurrent topics in Moritz Flaschel's work include Elasticity and Material Modeling (11 papers), Model Reduction and Neural Networks (8 papers) and Probabilistic and Robust Engineering Design (7 papers). Moritz Flaschel is often cited by papers focused on Elasticity and Material Modeling (11 papers), Model Reduction and Neural Networks (8 papers) and Probabilistic and Robust Engineering Design (7 papers). Moritz Flaschel collaborates with scholars based in Switzerland, Netherlands and Germany. Moritz Flaschel's co-authors include Laura De Lorenzis, Siddhant Kumar, Prakash Thakolkaran, Enzo Marino, Paul Steinmann, Pietro Carrara, Nikolaos Bouklas, WaiChing Sun, Nikolaos N. Vlassis and Jan N. Fuhg and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, Journal of the Mechanics and Physics of Solids and Applied Mechanics Reviews.

In The Last Decade

Moritz Flaschel

16 papers receiving 543 citations

Hit 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.

Automated discovery of generalized standard material models with EUCLID

2023 87 citations Moritz Flaschel, Siddhant Kumar et al. Computer Methods in Applied Mechanics and Engineering profile →
A Review on Data-Driven Constitutive Laws for Solids

2024 54 citations Jan N. Fuhg, Nikolaos Bouklas et al. Archives of Computational Methods in Engineering profile →

Peers

Moritz Flaschel

SNP

SPU

Rubén Ibáñez France

Nikolaos N. Vlassis United States

Karl A. Kalina Germany

M. Lefik Poland

F. Chinesta France

Ran Ma United States

M. Koishi Japan

Jack Hale Luxembourg

Hang Yang China

Christian Weißenfels Germany

Rubén Ibáñez France

Moritz Flaschel

246 ×0.8

SNP

159 ×0.5

189 ×0.8

138 ×1.1

SPU

139 ×1.3

Citations per year, relative to Moritz Flaschel Moritz Flaschel (= 1×) peers Rubén Ibáñez

Countries citing papers authored by Moritz Flaschel

Since Specialization

Citations

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

Fields of papers citing papers by Moritz Flaschel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Moritz Flaschel

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

All Works

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17 of 17 papers shown

Flaschel, Moritz, Paul Steinmann, Laura De Lorenzis, & Ellen Kuhl. (2025). Convex neural networks learn generalized standard material models. Journal of the Mechanics and Physics of Solids. 200. 106103–106103. 9 indexed citations

Flaschel, Moritz, et al.. (2025). Discovering non-associated pressure-sensitive plasticity models with EUCLID. Advanced Modeling and Simulation in Engineering Sciences. 12(1). 1–1. 3 indexed citations

Flaschel, Moritz, et al.. (2025). A topology optimisation framework to design test specimens for one-shot identification or discovery of material models. Journal of the Mechanics and Physics of Solids. 203. 106210–106210. 1 indexed citations

Römer, Ulrich, et al.. (2024). Reduced and All-At-Once Approaches for Model Calibration and Discovery in Computational Solid Mechanics. Applied Mechanics Reviews. 77(4). 13 indexed citations

Flaschel, Moritz, et al.. (2024). Data‐driven methods for quantitative imaging. GAMM-Mitteilungen. 48(1). 1 indexed citations

Fuhg, Jan N., Nikolaos Bouklas, WaiChing Sun, et al.. (2024). A review on data-driven constitutive laws for solids. arXiv (Cornell University). 1 indexed citations

Fuhg, Jan N., Nikolaos Bouklas, WaiChing Sun, et al.. (2024). A Review on Data-Driven Constitutive Laws for Solids. Archives of Computational Methods in Engineering. 32(3). 1841–1883. 54 indexed citations breakdown →

Flaschel, Moritz, et al.. (2023). Single-test evaluation of directional elastic properties of anisotropic structured materials. Journal of the Mechanics and Physics of Solids. 181. 105471–105471. 11 indexed citations

Marino, Enzo, Moritz Flaschel, Siddhant Kumar, & Laura De Lorenzis. (2023). Automated identification of linear viscoelastic constitutive laws with EUCLID. Mechanics of Materials. 181. 104643–104643. 32 indexed citations

10.

Flaschel, Moritz, et al.. (2023). Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID. Journal of the Mechanics and Physics of Solids. 180. 105404–105404. 31 indexed citations

11.

Flaschel, Moritz, Siddhant Kumar, & Laura De Lorenzis. (2023). Automated discovery of generalized standard material models with EUCLID. Computer Methods in Applied Mechanics and Engineering. 405. 115867–115867. 87 indexed citations breakdown →

12.

Thakolkaran, Prakash, et al.. (2022). Bayesian-EUCLID: discovering hyperelastic material laws with uncertainties. arXiv (Cornell University). 49 indexed citations

13.

Flaschel, Moritz, Siddhant Kumar, & Laura De Lorenzis. (2022). Automated discovery of generalized standard material models with EUCLID. SSRN Electronic Journal. 2 indexed citations

14.

Thakolkaran, Prakash, et al.. (2022). NN-EUCLID: Deep-learning hyperelasticity without stress data. Journal of the Mechanics and Physics of Solids. 169. 105076–105076. 107 indexed citations

15.

Flaschel, Moritz, Siddhant Kumar, & Laura De Lorenzis. (2022). Discovering plasticity models without stress data. npj Computational Materials. 8(1). 78 indexed citations

16.

Flaschel, Moritz, Siddhant Kumar, & Laura De Lorenzis. (2021). Unsupervised discovery of interpretable hyperelastic constitutive laws. Computer Methods in Applied Mechanics and Engineering. 381. 113852–113852. 153 indexed citations

17.

Flaschel, Moritz & Laura De Lorenzis. (2020). Calibration of material parameters based on 180$$^\circ $$ and 90$$^\circ $$ ferroelectric domain wall properties in Ginzburg–Landau–Devonshire phase field models. Archive of Applied Mechanics. 90(12). 2755–2774. 2 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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