André Röhm
Impact in
- Artificial Intelligence top 10%
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
Papers in
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- Neural Networks and Reservoir Computing 13
- Quantum Information and Cryptography 5
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- Nonlinear Dynamics and Pattern Formation 8
- Co-authors
- Kathy Lüdge (10 shared papers)Benjamin Lingnau (4 shared papers)Serhiy Yanchuk (1 shared paper)Fabian Böhm (1 shared paper)Lina Jaurigue (1 shared paper)Daniel J. Gauthier (2 shared papers)Makoto Naruse (14 shared papers)Ingo Fischer (2 shared papers)
In The Last Decade
André Röhm
26 papers receiving 301 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 183
- Statistical and Nonlinear Physics 46
- Electrical and Electronic Engineering 206
- Computer Networks and Communications 62
- Atomic and Molecular Physics, and Optics 75
Countries citing papers authored by André Röhm
This map shows the geographic impact of André Röhm'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 André Röhm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites André Röhm more than expected).
Fields of papers citing papers by André Röhm
This network shows the impact of papers produced by André Röhm. 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 André Röhm. The network helps show where André Röhm may publish in the future.
Co-authors
The 25 scholars most cited alongside André Röhm, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 48 | |
| 2 | 2016 | 33 | |
| 3 | 2018 | 31 | |
| 4 | 2019 | 26 | |
| 5 | 2014 | 22 | |
| 6 | 2022 | 22 | |
| 7 | 2017 | 21 | |
| 8 | 2021 | 18 | |
| 9 | 2018 | 15 | |
| 10 | 2015 | 14 | |
| 11 | 2021 | 11 | |
| 12 | 2014 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2015 | 8 | |
| 15 | 2022 | 4 | |
| 16 | 2023 | 4 | |
| 17 | 2023 | 3 | |
| 18 | 2023 | 3 | |
| 19 | 2023 | 2 | |
| 20 | 2019 | 2 |
About André Röhm
André Röhm is a scholar working on Artificial Intelligence, Computer Networks and Communications, Statistical and Nonlinear Physics, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics, having authored 28 papers that have together received 312 indexed citations. Recurring topics across this work include Neural Networks and Reservoir Computing (13 papers), Nonlinear Dynamics and Pattern Formation (8 papers), Optical Network Technologies (6 papers), Quantum Information and Cryptography (5 papers), Semiconductor Lasers and Optical Devices (5 papers), Semiconductor Quantum Structures and Devices (4 papers), Photonic and Optical Devices (4 papers) and Advanced Memory and Neural Computing (4 papers). The work is most often cited by research in Artificial Intelligence (183 citations), Statistical and Nonlinear Physics (46 citations), Electrical and Electronic Engineering (206 citations), Computer Networks and Communications (62 citations) and Atomic and Molecular Physics, and Optics (75 citations). André Röhm has collaborated with scholars based in Japan, Germany and Spain. Frequent co-authors include Kathy Lüdge, Benjamin Lingnau, Serhiy Yanchuk, Fabian Böhm, Lina Jaurigue, Daniel J. Gauthier, Makoto Naruse, Ingo Fischer, Ryoichi Horisaki and Miguel Cornelles Soriano. Their work appears in journals such as Chaos An Interdisciplinary Journal of Nonlinear Science, Physical review. E, Complexity, Applied Physics Letters and Annalen der Physik.
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.