Leon Herrmann
Impact in
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- Model Reduction and Neural Networks
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- Ultrasonics and Acoustic Wave Propagation
- Composite Material Mechanics
Papers in
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- Model Reduction and Neural Networks 6
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- Numerical methods in engineering 4
- Mechanical Behavior of Composites 3
- Ultrasonics and Acoustic Wave Propagation 3
- Co-authors
- Stefan Kollmannsberger (15 shared papers)Davide D’Angella (7 shared papers)Felix Dietrich (2 shared papers)V. Li (1 shared paper)C. Vogl (1 shared paper)Henning Wessels (1 shared paper)Ole Sigmund (1 shared paper)Divya Singh (1 shared paper)
- Journals
- Computational Mechanics (4 papers)Structural and Multidisciplinary Optimization (1 paper)Composites Science and Technology (1 paper)Composites Part B Engineering (1 paper)Engineering Applications of Artificial Intelligence (1 paper)
- Partner nations
- GermanySwitzerlandDenmark
In The Last Decade
Leon Herrmann
19 papers receiving 189 citations
Leon Herrmann's Hit Papers
Peers
Comparison fields: 5 of 44
- Statistical and Nonlinear Physics 73
- Mechanics of Materials 52
- Ocean Engineering 23
- Civil and Structural Engineering 29
- Geophysics 17
Countries citing papers authored by Leon Herrmann
This map shows the geographic impact of Leon Herrmann'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 Leon Herrmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leon Herrmann more than expected).
Fields of papers citing papers by Leon Herrmann
This network shows the impact of papers produced by Leon Herrmann. 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 Leon Herrmann. The network helps show where Leon Herrmann may publish in the future.
Co-authors
The 15 scholars most cited alongside Leon Herrmann, 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 | Deep learning in computational mechanics: a review Hit paper breakdown → | 2024 | 71 |
| 2 | 2021 | 42 | |
| 3 | 2021 | 22 | |
| 4 | 2023 | 14 | |
| 5 | 2024 | 10 | |
| 6 | 2023 | 6 | |
| 7 | 2021 | 6 | |
| 8 | 2024 | 6 | |
| 9 | 2021 | 4 | |
| 10 | 2022 | 3 | |
| 11 | 2025 | 2 | |
| 12 | 2022 | 2 | |
| 13 | 2021 | 2 | |
| 14 | 2022 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2021 | 1 | |
| 18 | 2021 | 1 | |
| 19 | 2022 | 1 | |
| 20 | 2017 | 0 |
About Leon Herrmann
Leon Herrmann is a scholar working on Statistical and Nonlinear Physics, Mechanics of Materials, Artificial Intelligence, Mechanical Engineering and Geophysics, having authored 20 papers that have together received 197 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (6 papers), Numerical methods in engineering (4 papers), Mechanical Behavior of Composites (3 papers), Seismic Imaging and Inversion Techniques (3 papers), Ultrasonics and Acoustic Wave Propagation (3 papers), Geophysical Methods and Applications (2 papers), Structural Health Monitoring Techniques (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (73 citations), Mechanics of Materials (52 citations), Ocean Engineering (23 citations), Civil and Structural Engineering (29 citations) and Geophysics (17 citations). Leon Herrmann has collaborated with scholars based in Germany, Switzerland and Denmark. Frequent co-authors include Stefan Kollmannsberger, Davide D’Angella, Felix Dietrich, V. Li, C. Vogl, Henning Wessels, Ole Sigmund, Divya Singh, Christian F. Niordson and Adelinde M. Uhrmacher. Their work appears in journals such as Computational Mechanics, Structural and Multidisciplinary Optimization, Composites Science and Technology, Composites Part B Engineering and Engineering Applications of Artificial Intelligence.
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.