Erik Buhmann
Impact in
- Nuclear and High Energy Physics top 10%
- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Particle Detector Development and Performance
- Quantum Chromodynamics and Particle Interactions
- Dark Matter and Cosmic Phenomena
- Artificial Intelligence top 10%
- Computational Physics and Python Applications
- Gaussian Processes and Bayesian Inference
Papers in
-
- Particle physics theoretical and experimental studies 10
- High-Energy Particle Collisions Research 6
- Particle Detector Development and Performance 4
- Dark Matter and Cosmic Phenomena 1
-
- Computational Physics and Python Applications 5
- Co-authors
- Gregor Kasieczka (10 shared papers)K. Krüger (7 shared papers)Frank Gaede (7 shared papers)Sascha Diefenbacher (6 shared papers)Engin Eren (6 shared papers)W. Korcari (6 shared papers)Jesse Thaler (1 shared paper)L. Rustige (3 shared papers)
- Journals
- Physical review. D (2 papers)Journal of Instrumentation (2 papers)SciPost Physics (1 paper)Machine Learning Science and Technology (1 paper)Science and Global Security (1 paper)
- Partner nations
- GermanyUnited StatesUkraine
In The Last Decade
Erik Buhmann
12 papers receiving 290 citations
Peers
Comparison fields: 5 of 25
- Nuclear and High Energy Physics 227
- Artificial Intelligence 95
- Radiation 23
- Computer Vision and Pattern Recognition 41
- Statistical and Nonlinear Physics 24
Countries citing papers authored by Erik Buhmann
This map shows the geographic impact of Erik Buhmann'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 Erik Buhmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erik Buhmann more than expected).
Fields of papers citing papers by Erik Buhmann
This network shows the impact of papers produced by Erik Buhmann. 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 Erik Buhmann. The network helps show where Erik Buhmann may publish in the future.
Co-authors
The 23 scholars most cited alongside Erik Buhmann, 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 | 2021 | 72 | |
| 2 | 2021 | 43 | |
| 3 | 2022 | 43 | |
| 4 | 2023 | 36 | |
| 5 | 2023 | 36 | |
| 6 | 2024 | 17 | |
| 7 | 2024 | 16 | |
| 8 | 2022 | 10 | |
| 9 | 2021 | 10 | |
| 10 | 2025 | 4 | |
| 11 | 2023 | 2 | |
| 12 | 2018 | 1 |
About Erik Buhmann
Erik Buhmann is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Computational Mechanics, Aerospace Engineering and Political Science and International Relations, having authored 12 papers that have together received 290 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (10 papers), High-Energy Particle Collisions Research (6 papers), Computational Physics and Python Applications (5 papers), Particle Detector Development and Performance (4 papers), Dark Matter and Cosmic Phenomena (1 paper), Nuclear and radioactivity studies (1 paper), Nuclear reactor physics and engineering (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (227 citations), Artificial Intelligence (95 citations), Radiation (23 citations), Computer Vision and Pattern Recognition (41 citations) and Statistical and Nonlinear Physics (24 citations). Erik Buhmann has collaborated with scholars based in Germany, United States and Ukraine. Frequent co-authors include Gregor Kasieczka, K. Krüger, Frank Gaede, Sascha Diefenbacher, Engin Eren, W. Korcari, Jesse Thaler, L. Rustige, David Shih and V. M. Mikuni. Their work appears in journals such as Physical review. D, Journal of Instrumentation, SciPost Physics, Machine Learning Science and Technology and Science and Global Security.
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.