Daniel Matthes
Impact in
- Applied Mathematics top 2%
- Geometric Analysis and Curvature Flows
- Nonlinear Partial Differential Equations
- Modeling and Simulation top 2%
- Mathematical Biology Tumor Growth
Papers in
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- Geometric Analysis and Curvature Flows 15
- Nonlinear Partial Differential Equations 12
- Gas Dynamics and Kinetic Theory 8
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- Advanced Thermodynamics and Statistical Mechanics 8
- Co-authors
- Giuseppe Toscani (8 shared papers)Ansgar Jüngel (9 shared papers)Stefanie Hoehl (7 shared papers)Bertram Düring (5 shared papers)Ezgi Kayhan (4 shared papers)Giuseppe Savaré (3 shared papers)Trinh Nguyen (3 shared papers)Pascal Vrtička (2 shared papers)
In The Last Decade
Daniel Matthes
53 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 101
- Applied Mathematics 328
- Modeling and Simulation 114
- Statistical and Nonlinear Physics 235
- Mathematical Physics 147
- Cognitive Neuroscience 187
Countries citing papers authored by Daniel Matthes
This map shows the geographic impact of Daniel Matthes'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 Daniel Matthes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Matthes more than expected).
Fields of papers citing papers by Daniel Matthes
This network shows the impact of papers produced by Daniel Matthes. 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 Daniel Matthes. The network helps show where Daniel Matthes may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Matthes, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 138 | |
| 2 | 2020 | 93 | |
| 3 | 2008 | 87 | |
| 4 | 2009 | 83 | |
| 5 | 2007 | 80 | |
| 6 | 2008 | 53 | |
| 7 | 2007 | 42 | |
| 8 | 2006 | 40 | |
| 9 | 2012 | 39 | |
| 10 | 2006 | 39 | |
| 11 | 2013 | 30 | |
| 12 | 2005 | 25 | |
| 13 | 2015 | 23 | |
| 14 | 2017 | 21 | |
| 15 | 2010 | 20 | |
| 16 | 2015 | 20 | |
| 17 | 2022 | 17 | |
| 18 | 2018 | 17 | |
| 19 | 2008 | 16 | |
| 20 | 2003 | 16 |
About Daniel Matthes
Daniel Matthes is a scholar working on Applied Mathematics, Statistical and Nonlinear Physics, Computational Mechanics, Mathematical Physics and Social Psychology, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Geometric Analysis and Curvature Flows (15 papers), Nonlinear Partial Differential Equations (12 papers), Fluid Dynamics and Turbulent Flows (10 papers), Advanced Thermodynamics and Statistical Mechanics (8 papers), Gas Dynamics and Kinetic Theory (8 papers), Advanced Mathematical Modeling in Engineering (6 papers), Advanced Mathematical Physics Problems (5 papers) and Action Observation and Synchronization (4 papers). The work is most often cited by research in Applied Mathematics (328 citations), Modeling and Simulation (114 citations), Statistical and Nonlinear Physics (235 citations), Mathematical Physics (147 citations) and Cognitive Neuroscience (187 citations). Daniel Matthes has collaborated with scholars based in Germany, Austria and Italy. Frequent co-authors include Giuseppe Toscani, Ansgar Jüngel, Stefanie Hoehl, Bertram Düring, Ezgi Kayhan, Giuseppe Savaré, Trinh Nguyen, Pascal Vrtička, Hanna Schleihauf and Robert J. McCann. Their work appears in journals such as Nonlinearity, Comptes Rendus Mathématique, SIAM Journal on Mathematical Analysis, Archive for Rational Mechanics and Analysis and Cortex.
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.