Joseph Abbate
Impact in
- Nuclear and High Energy Physics top 10%
- Magnetic confinement fusion research
-
- Nuclear Physics and Applications
Papers in
-
- Magnetic confinement fusion research 10
-
- Nuclear reactor physics and engineering 6
- Co-authors
- Egemen Kolemen (12 shared papers)Rory Conlin (6 shared papers)Keith Erickson (5 shared papers)Azarakhsh Jalalvand (5 shared papers)Brian R. Reid (2 shared papers)N. Susan Ribeiro (2 shared papers)Ricardo Shousha (3 shared papers)Ralph E. Hurd (2 shared papers)
- Journals
- Nuclear Fusion (6 papers)Biochemistry (2 papers)Analytical Biochemistry (1 paper)Engineering Applications of Artificial Intelligence (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Joseph Abbate
16 papers receiving 252 citations
Peers
Comparison fields: 5 of 81
- Nuclear and High Energy Physics 123
- Radiation 23
- Statistical and Nonlinear Physics 16
- Aerospace Engineering 32
- Artificial Intelligence 38
Countries citing papers authored by Joseph Abbate
This map shows the geographic impact of Joseph Abbate'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 Joseph Abbate with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph Abbate more than expected).
Fields of papers citing papers by Joseph Abbate
This network shows the impact of papers produced by Joseph Abbate. 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 Joseph Abbate. The network helps show where Joseph Abbate may publish in the future.
Co-authors
The 25 scholars most cited alongside Joseph Abbate, 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 | 2024 | 64 | |
| 2 | 2021 | 34 | |
| 3 | 1979 | 29 | |
| 4 | 2021 | 24 | |
| 5 | 1977 | 22 | |
| 6 | 2021 | 20 | |
| 7 | 2021 | 20 | |
| 8 | 2023 | 18 | |
| 9 | 1972 | 16 | |
| 10 | 2022 | 8 | |
| 11 | 2024 | 6 | |
| 12 | 2024 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2024 | 3 | |
| 15 | 2023 | 3 | |
| 16 | 2025 | 2 | |
| 17 | Study on determining stability domains for nonlinear dynamical systems Final report 1 May 1966 - 1 Feb. 1967 | 1967 | 1 |
| 18 | The Mobile Monitoring of Particulate Matter through Wearable Sensors and Their Influence on Students' Environmental Attitudes | 2017 | 0 |
About Joseph Abbate
Joseph Abbate is a scholar working on Nuclear and High Energy Physics, Aerospace Engineering, Materials Chemistry, Molecular Biology and Statistical and Nonlinear Physics, having authored 18 papers that have together received 280 indexed citations. Recurring topics across this work include Magnetic confinement fusion research (10 papers), Nuclear reactor physics and engineering (6 papers), Fusion materials and technologies (5 papers), Superconducting Materials and Applications (2 papers), Environmental Education and Sustainability (2 papers), Nuclear Physics and Applications (2 papers), Neural Networks and Reservoir Computing (2 papers) and Model Reduction and Neural Networks (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (123 citations), Radiation (23 citations), Statistical and Nonlinear Physics (16 citations), Aerospace Engineering (32 citations) and Artificial Intelligence (38 citations). Joseph Abbate has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Egemen Kolemen, Rory Conlin, Keith Erickson, Azarakhsh Jalalvand, Brian R. Reid, N. Susan Ribeiro, Ricardo Shousha, Ralph E. Hurd, Jaemin Seo and S.K. Kim. Their work appears in journals such as Nuclear Fusion, Biochemistry, Analytical Biochemistry, Engineering Applications of Artificial Intelligence and IEEE Transactions on Neural Networks and Learning Systems.
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.