M. Plum
Impact in
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- Astrophysics and Cosmic Phenomena
- Dark Matter and Cosmic Phenomena
- Particle Detector Development and Performance
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- Computational Physics and Python Applications
Papers in
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- Neutrino Physics Research 4
- Astrophysics and Cosmic Phenomena 4
- Dark Matter and Cosmic Phenomena 3
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- Computational Physics and Python Applications 2
- Co-authors
- K. Andeen (2 shared papers)A. Hinzmann (2 shared papers)T. Klimkovich (2 shared papers)O. Actis (2 shared papers)M. Erdmann (2 shared papers)J. Steggemann (2 shared papers)M. Kirsch (1 shared paper)Thomas Münzer (1 shared paper)
- Journals
- Journal of Physics Conference Series (1 paper)Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019) (2 papers)EPJ Web of Conferences (2 papers)
- Partner nations
- United StatesGermany
In The Last Decade
M. Plum
5 papers receiving 8 citations
Peers
Comparison fields: 5 of 6
- Nuclear and High Energy Physics 7
- Artificial Intelligence 4
- Astronomy and Astrophysics 2
- Computer Vision and Pattern Recognition 2
- Computer Networks and Communications 2
Countries citing papers authored by M. Plum
This map shows the geographic impact of M. Plum'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 M. Plum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Plum more than expected).
Fields of papers citing papers by M. Plum
This network shows the impact of papers produced by M. Plum. 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 M. Plum. The network helps show where M. Plum may publish in the future.
Co-authors
The 12 scholars most cited alongside M. Plum, 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 | 2010 | 5 | |
| 2 | 2019 | 2 | |
| 3 | 2019 | 1 | |
| 4 | 2009 | 1 | |
| 5 | 2019 | 1 | |
| 6 | 2023 | 0 |
About M. Plum
M. Plum is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Computer Networks and Communications, Information Systems and Management and Infectious Diseases, having authored 6 papers that have together received 10 indexed citations. Recurring topics across this work include Neutrino Physics Research (4 papers), Astrophysics and Cosmic Phenomena (4 papers), Dark Matter and Cosmic Phenomena (3 papers), Computational Physics and Python Applications (2 papers), Scientific Computing and Data Management (1 paper), Distributed and Parallel Computing Systems (1 paper), Big Data Technologies and Applications (1 paper) and Advanced Data Storage Technologies (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (7 citations), Artificial Intelligence (4 citations), Astronomy and Astrophysics (2 citations), Computer Vision and Pattern Recognition (2 citations) and Computer Networks and Communications (2 citations). M. Plum has collaborated with scholars based in United States and Germany. Frequent co-authors include K. Andeen, A. Hinzmann, T. Klimkovich, O. Actis, M. Erdmann, J. Steggemann, M. Kirsch, Thomas Münzer, Gero Müller and Robert Fischer. Their work appears in journals such as Journal of Physics Conference Series, Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019) and EPJ Web of Conferences.
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.