P. Parygin
Impact in
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- Radiation Detection and Scintillator Technologies
- Nuclear Physics and Applications
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- Particle Detector Development and Performance
Papers in
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- Anomaly Detection Techniques and Applications 4
- Neural Networks and Applications 1
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- COVID-19 diagnosis using AI 3
- Co-authors
- V. Popov (1 shared paper)R. Klanner (1 shared paper)Marco Ramilli (1 shared paper)E. Garutti (3 shared papers)A. Khukhunaishvili (2 shared papers)S. I. Cooper (3 shared papers)David S. Yu (1 shared paper)J. Dittmann (5 shared papers)
- Journals
- Sensors (2 papers)Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment (2 papers)Journal of Instrumentation (1 paper)PHM Society European Conference (1 paper)
- Partner nations
- United StatesNorwayRussia
In The Last Decade
P. Parygin
7 papers receiving 31 citations
Peers
Comparison fields: 5 of 17
- Radiation 14
- Nuclear and High Energy Physics 10
- Instrumentation 2
- Artificial Intelligence 12
- Radiology, Nuclear Medicine and Imaging 5
Countries citing papers authored by P. Parygin
This map shows the geographic impact of P. Parygin'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 P. Parygin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. Parygin more than expected).
Fields of papers citing papers by P. Parygin
This network shows the impact of papers produced by P. Parygin. 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 P. Parygin. The network helps show where P. Parygin may publish in the future.
Co-authors
The 25 scholars most cited alongside P. Parygin, 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 | 2014 | 13 | |
| 2 | 2021 | 5 | |
| 3 | 2023 | 4 | |
| 4 | 2022 | 3 | |
| 5 | 2022 | 3 | |
| 6 | 2022 | 2 | |
| 7 | 2024 | 1 | |
| 8 | 2025 | 0 |
About P. Parygin
P. Parygin is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering, Nuclear and High Energy Physics and Computer Networks and Communications, having authored 8 papers that have together received 31 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), COVID-19 diagnosis using AI (3 papers), Integrated Circuits and Semiconductor Failure Analysis (2 papers), Particle Detector Development and Performance (2 papers), Semiconductor materials and devices (2 papers), Data-Driven Disease Surveillance (1 paper), Neutrino Physics Research (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Radiation (14 citations), Nuclear and High Energy Physics (10 citations), Instrumentation (2 citations), Artificial Intelligence (12 citations) and Radiology, Nuclear Medicine and Imaging (5 citations). P. Parygin has collaborated with scholars based in United States, Norway and Russia. Frequent co-authors include V. Popov, R. Klanner, Marco Ramilli, E. Garutti, A. Khukhunaishvili, S. I. Cooper, David S. Yu, J. Dittmann, A. Stifutkin and O. Bychkova. Their work appears in journals such as Sensors, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Journal of Instrumentation and PHM Society European Conference.
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.