Paul J. Nahin
- Artificial Intelligence
- Atomic and Molecular Physics, and Optics
- Astronomy and Astrophysics
- History and Philosophy of Science top 5%
- Statistical and Nonlinear Physics
- Topics
- Historical Philosophy and Science (2 papers)Computational Physics and Python Applications (2 papers)Natural Language Processing Techniques (2 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceProceedings of the IEEEPattern Recognition
- Partner nations
- United StatesUnited KingdomPhilippines
In The Last Decade
Paul J. Nahin
43 papers receiving 251 citations
Peers
Comparison fields: 5 of 99
- Artificial Intelligence 41
- Atomic and Molecular Physics, and Optics 37
- Astronomy and Astrophysics 28
- History and Philosophy of Science 25
- Statistical and Nonlinear Physics 25
Countries citing papers authored by Paul J. Nahin
This map shows the geographic impact of Paul J. Nahin'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 Paul J. Nahin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul J. Nahin more than expected).
Fields of papers citing papers by Paul J. Nahin
This network shows the impact of papers produced by Paul J. Nahin. 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 Paul J. Nahin. The network helps show where Paul J. Nahin may publish in the future.
Co-authorship network of co-authors of Paul J. Nahin
This figure shows the co-authorship network connecting the top 25 collaborators of Paul J. Nahin. A scholar is included among the top collaborators of Paul J. Nahin 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 Paul J. Nahin. Paul J. Nahin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 6 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 7 | |
| 14 | When Least Is Best | 7 |
| 15 | 16 | |
| 16 | 1 | |
| 17 | 4 | |
| 18 | Oliver Heaviside : genius and curmudgeon | 4 |
| 19 | 1 | |
| 20 | 9 |
About Paul J. Nahin
Paul J. Nahin is a scholar working on Theoretical Computer Science, History and Philosophy of Science and Computer Graphics and Computer-Aided Design, having authored 52 papers that have together received 291 indexed citations. Recurring topics across this work include Historical Philosophy and Science (2 papers), Computational Physics and Python Applications (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Theoretical Computer Science (23 citations), History and Philosophy of Science (25 citations) and Modeling and Simulation (16 citations). Paul J. Nahin has collaborated with scholars based in United States, United Kingdom and Philippines. Frequent co-authors include Jack Sklansky, Charles Seife, Eli Maor and Robert E. Kaplan. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the IEEE and Pattern Recognition.
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.