J. Pazzini
Impact in
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- Particle physics theoretical and experimental studies
- Particle Detector Development and Performance
Papers in
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- Quantum, superfluid, helium dynamics 4
- Atomic and Subatomic Physics Research 3
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- Particle physics theoretical and experimental studies 6
- Particle Detector Development and Performance 4
- Dark Matter and Cosmic Phenomena 3
- Co-authors
- Lisa Solieri (1 shared paper)Paolo Giudici (1 shared paper)Tikam Chand Dakal (1 shared paper)Stefano Cassanelli (1 shared paper)M. Zanetti (11 shared papers)A. Zucchetta (4 shared papers)Matteo Migliorini (6 shared papers)Andrea Triossi (7 shared papers)
- Journals
- Journal of Instrumentation (3 papers)Machine Learning Science and Technology (2 papers)The Journal of Chemical Physics (2 papers)Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment (2 papers)FEMS Yeast Research (1 paper)
- Partner nations
- ItalySwitzerlandFrance
In The Last Decade
J. Pazzini
11 papers receiving 49 citations
Peers
Comparison fields: 5 of 23
- Nuclear and High Energy Physics 12
- Hardware and Architecture 4
- Food Science 10
- Biotechnology 3
- Molecular Biology 20
Countries citing papers authored by J. Pazzini
This map shows the geographic impact of J. Pazzini'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 J. Pazzini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Pazzini more than expected).
Fields of papers citing papers by J. Pazzini
This network shows the impact of papers produced by J. Pazzini. 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 J. Pazzini. The network helps show where J. Pazzini may publish in the future.
Co-authors
The 25 scholars most cited alongside J. Pazzini, 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 | 2016 | 22 | |
| 2 | 2022 | 10 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 3 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 2 | |
| 7 | 2016 | 1 | |
| 8 | 2025 | 1 | |
| 9 | 2024 | 1 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 1 | |
| 12 | 2025 | 0 | |
| 13 | 2025 | 0 | |
| 14 | 2023 | 0 | |
| 15 | 2022 | 0 | |
| 16 | 2025 | 0 |
About J. Pazzini
J. Pazzini is a scholar working on Atomic and Molecular Physics, and Optics, Nuclear and High Energy Physics, Computer Networks and Communications, Artificial Intelligence and Hardware and Architecture, having authored 16 papers that have together received 49 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (6 papers), Particle Detector Development and Performance (4 papers), Quantum, superfluid, helium dynamics (4 papers), Dark Matter and Cosmic Phenomena (3 papers), Atomic and Subatomic Physics Research (3 papers), Parallel Computing and Optimization Techniques (2 papers), Advanced Data Storage Technologies (2 papers) and High-pressure geophysics and materials (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (12 citations), Hardware and Architecture (4 citations), Food Science (10 citations), Biotechnology (3 citations) and Molecular Biology (20 citations). J. Pazzini has collaborated with scholars based in Italy, Switzerland and France. Frequent co-authors include Lisa Solieri, Paolo Giudici, Tikam Chand Dakal, Stefano Cassanelli, M. Zanetti, A. Zucchetta, Matteo Migliorini, Andrea Triossi, Andrea Wulzer and A. F. Borghesani. Their work appears in journals such as Journal of Instrumentation, Machine Learning Science and Technology, The Journal of Chemical Physics, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and FEMS Yeast Research.
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.