G. Dezoort
Impact in
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- Particle physics theoretical and experimental studies
- Particle Detector Development and Performance
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- Scientific Computing and Data Management
Papers in
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- Particle Accelerators and Free-Electron Lasers 1
- Radiation Effects in Electronics 1
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- Particle Detector Development and Performance 3
- Particle physics theoretical and experimental studies 2
- Co-authors
- Peter Battaglia (1 shared paper)C. Biscarat (1 shared paper)Jean-Roch Vlimant (1 shared paper)I. Ojalvo (1 shared paper)Markus Julian Atkinson (1 shared paper)Bo‐Cheng Lai (1 shared paper)J. Duarte (1 shared paper)M. S. Neubauer (1 shared paper)
- Journals
- Nature Reviews Physics (1 paper)Frontiers in Big Data (1 paper)EPJ Web of Conferences (1 paper)SIAM Journal on Mathematics of Data Science (1 paper)Bulletin of the American Physical Society (1 paper)
- Partner nations
- United StatesTaiwanFrance
In The Last Decade
G. Dezoort
3 papers receiving 48 citations
Peers
Comparison fields: 5 of 24
- Nuclear and High Energy Physics 22
- Information Systems and Management 5
- Hardware and Architecture 4
- Artificial Intelligence 19
- Computer Vision and Pattern Recognition 9
Countries citing papers authored by G. Dezoort
This map shows the geographic impact of G. Dezoort'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 G. Dezoort with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Dezoort more than expected).
Fields of papers citing papers by G. Dezoort
This network shows the impact of papers produced by G. Dezoort. 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 G. Dezoort. The network helps show where G. Dezoort may publish in the future.
Co-authors
The 16 scholars most cited alongside G. Dezoort, 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 | 2023 | 23 | |
| 2 | 2022 | 23 | |
| 3 | 2024 | 2 | |
| 4 | The CMS electron and photon trigger for the LHC Run 2 | 2017 | 0 |
| 5 | 2025 | 0 |
About G. Dezoort
G. Dezoort is a scholar working on Electrical and Electronic Engineering, Nuclear and High Energy Physics, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 48 indexed citations. Recurring topics across this work include Particle Detector Development and Performance (3 papers), Particle physics theoretical and experimental studies (2 papers), Medical Imaging Techniques and Applications (2 papers), Adversarial Robustness in Machine Learning (1 paper), Particle Accelerators and Free-Electron Lasers (1 paper), Radiation Effects in Electronics (1 paper), Neural Networks and Applications (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (22 citations), Information Systems and Management (5 citations), Hardware and Architecture (4 citations), Artificial Intelligence (19 citations) and Computer Vision and Pattern Recognition (9 citations). G. Dezoort has collaborated with scholars based in United States, Taiwan and France. Frequent co-authors include Peter Battaglia, C. Biscarat, Jean-Roch Vlimant, I. Ojalvo, Markus Julian Atkinson, Bo‐Cheng Lai, J. Duarte, M. S. Neubauer, Shi‐Yu Huang and S. J. Thais. Their work appears in journals such as Nature Reviews Physics, Frontiers in Big Data, EPJ Web of Conferences, SIAM Journal on Mathematics of Data Science and Bulletin of the American Physical Society.
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.