F. Ruffini
Impact in
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- Oil and Gas Production Techniques
Papers in
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- Privacy-Preserving Technologies in Data 5
- Explainable Artificial Intelligence (XAI) 4
- Solar Radiation and Photovoltaics 2
- Anomaly Detection Techniques and Applications 2
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- Water Systems and Optimization 2
- Co-authors
- Mauro Tucci (2 shared papers)Alessandro Betti (1 shared paper)Emanuele Crisostomi (2 shared papers)Pietro Ducange (6 shared papers)Alessandro Renda (6 shared papers)Francesco Marcelloni (8 shared papers)Giovanni Stea (1 shared paper)Antonio Virdis (1 shared paper)
- Journals
- IEEE Access (2 papers)Information Systems Frontiers (1 paper)Renewable Energy (1 paper)Environmental Impact Assessment Review (1 paper)Cognitive Computation (1 paper)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
F. Ruffini
12 papers receiving 125 citations
Peers
Comparison fields: 5 of 58
- Health Informatics 8
- Ocean Engineering 19
- Artificial Intelligence 34
- Nephrology 6
- Control and Systems Engineering 20
Countries citing papers authored by F. Ruffini
This map shows the geographic impact of F. Ruffini'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 F. Ruffini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F. Ruffini more than expected).
Fields of papers citing papers by F. Ruffini
This network shows the impact of papers produced by F. Ruffini. 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 F. Ruffini. The network helps show where F. Ruffini may publish in the future.
Co-authors
The 25 scholars most cited alongside F. Ruffini, 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 | 2021 | 53 | |
| 2 | 2023 | 28 | |
| 3 | 2009 | 14 | |
| 4 | 2024 | 10 | |
| 5 | 2020 | 9 | |
| 6 | 2016 | 4 | |
| 7 | 2014 | 4 | |
| 8 | 2025 | 2 | |
| 9 | Web tools for performance analysis and planning support for solar energy plants (PV, CSP, CPV) starting from remotely sensed optical images | 2013 | 2 |
| 10 | 2024 | 1 | |
| 11 | 2023 | 1 | |
| 12 | 2020 | 1 | |
| 13 | 2026 | 0 | |
| 14 | 2024 | 0 | |
| 15 | 2026 | 0 |
About F. Ruffini
F. Ruffini is a scholar working on Artificial Intelligence, Civil and Structural Engineering, Control and Systems Engineering, Computer Vision and Pattern Recognition and Health Informatics, having authored 15 papers that have together received 129 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (5 papers), Explainable Artificial Intelligence (XAI) (4 papers), Water Systems and Optimization (2 papers), Solar Radiation and Photovoltaics (2 papers), Solar Thermal and Photovoltaic Systems (2 papers), Photovoltaic System Optimization Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (8 citations), Ocean Engineering (19 citations), Artificial Intelligence (34 citations), Nephrology (6 citations) and Control and Systems Engineering (20 citations). F. Ruffini has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Mauro Tucci, Alessandro Betti, Emanuele Crisostomi, Pietro Ducange, Alessandro Renda, Francesco Marcelloni, Giovanni Stea, Antonio Virdis, Giovanni Nardini and Valeria Manfreda. Their work appears in journals such as IEEE Access, Information Systems Frontiers, Renewable Energy, Environmental Impact Assessment Review and Cognitive Computation.
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.