J. Pivarski
- Nuclear and High Energy Physics
- Computer Networks and Communications
- Information Systems and Management
- Artificial Intelligence
- Information Systems
- Co-authors
- Robert L. GrossmanA. SafonovA. BelyaevS. SenkinP. ElmerH.-P. DembinskiD. J. LangeM. L. Proffitt
- Topics
- Particle physics theoretical and experimental studies (5 papers)Computational Physics and Python Applications (5 papers)Distributed and Parallel Computing Systems (3 papers)
- Cited by
- Nuclear and High Energy PhysicsInformation Systems and ManagementComputer Networks and Communications
- Journals
- SHILAP Revista de lepidopterologíaInternational Journal of Data Science and AnalyticsJournal of Physics Conference Series
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
J. Pivarski
15 papers receiving 100 citations
Peers
Comparison fields: 5 of 29
- Nuclear and High Energy Physics 56
- Computer Networks and Communications 30
- Information Systems and Management 19
- Artificial Intelligence 19
- Information Systems 10
Countries citing papers authored by J. Pivarski
This map shows the geographic impact of J. Pivarski'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. Pivarski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Pivarski more than expected).
Fields of papers citing papers by J. Pivarski
This network shows the impact of papers produced by J. Pivarski. 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. Pivarski. The network helps show where J. Pivarski may publish in the future.
Co-authorship network of co-authors of J. Pivarski
This figure shows the co-authorship network connecting the top 25 collaborators of J. Pivarski. A scholar is included among the top collaborators of J. Pivarski based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with J. Pivarski. J. Pivarski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 17 | |
| 8 | 6 | |
| 9 | 0 | |
| 10 | Tintenfisch: File System Namespace Schemas and Generators | 1 |
| 11 | Fast Access to Columnar, Hierarchical Data via Code Transformation. | 1 |
| 12 | 2 | |
| 13 | 2 | |
| 14 | 4 | |
| 15 | 1 | |
| 16 | 0 | |
| 17 | 24 | |
| 18 | 28 |
About J. Pivarski
J. Pivarski is a scholar working on Information Systems and Management, Nuclear and High Energy Physics and Hardware and Architecture, having authored 18 papers that have together received 103 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (5 papers), Computational Physics and Python Applications (5 papers) and Distributed and Parallel Computing Systems (3 papers). The work is most often cited by research in Nuclear and High Energy Physics (56 citations), Information Systems and Management (19 citations) and Computer Networks and Communications (30 citations). J. Pivarski has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Robert L. Grossman, A. Safonov, A. Belyaev, S. Senkin, P. Elmer, H.-P. Dembinski, D. J. Lange, M. L. Proffitt, Brian Bockelman and E. Rodrigues. Their work appears in journals such as SHILAP Revista de lepidopterología, International Journal of Data Science and Analytics and Journal of Physics Conference Series.
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.