Stefano Pagani
- Cardiology and Cardiovascular Medicine top 10%
- Statistical and Nonlinear Physics top 5%
- Statistics, Probability and Uncertainty top 5%
- Computational Mechanics
- Artificial Intelligence
- Co-authors
- Alfio QuarteroniAndrea ManzoniLuca Dede’Francesco RegazzoniMatteo SalvadorToni LassilaAntonio FronteraPaolo Della Bella
- Topics
- Cardiac electrophysiology and arrhythmias (11 papers)Model Reduction and Neural Networks (10 papers)Probabilistic and Robust Engineering Design (8 papers)
- Cited by
- Statistical and Nonlinear PhysicsStatistics, Probability and UncertaintyCardiology and Cardiovascular Medicine
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaJournal of Computational Physics
- Partner nations
- ItalySwitzerlandUnited States
In The Last Decade
Stefano Pagani
21 papers receiving 325 citations
Peers
Comparison fields: 5 of 53
- Cardiology and Cardiovascular Medicine 159
- Statistical and Nonlinear Physics 126
- Statistics, Probability and Uncertainty 60
- Computational Mechanics 53
- Artificial Intelligence 33
Countries citing papers authored by Stefano Pagani
This map shows the geographic impact of Stefano Pagani'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 Stefano Pagani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Pagani more than expected).
Fields of papers citing papers by Stefano Pagani
This network shows the impact of papers produced by Stefano Pagani. 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 Stefano Pagani. The network helps show where Stefano Pagani may publish in the future.
Co-authorship network of co-authors of Stefano Pagani
This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Pagani. A scholar is included among the top collaborators of Stefano Pagani 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 Stefano Pagani. Stefano Pagani 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 | 7 | |
| 3 | 0 | |
| 4 | 17 | |
| 5 | 9 | |
| 6 | 18 | |
| 7 | 16 | |
| 8 | 32 | |
| 9 | 26 | |
| 10 | 12 | |
| 11 | 6 | |
| 12 | 14 | |
| 13 | 13 | |
| 14 | 9 | |
| 15 | 20 | |
| 16 | 26 | |
| 17 | 3 | |
| 18 | 42 | |
| 19 | 18 | |
| 20 | 30 |
About Stefano Pagani
Stefano Pagani is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Cardiology and Cardiovascular Medicine, having authored 23 papers that have together received 337 indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (11 papers), Model Reduction and Neural Networks (10 papers) and Probabilistic and Robust Engineering Design (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (126 citations), Statistics, Probability and Uncertainty (60 citations) and Cardiology and Cardiovascular Medicine (159 citations). Stefano Pagani has collaborated with scholars based in Italy, Switzerland and United States. Frequent co-authors include Alfio Quarteroni, Andrea Manzoni, Luca Dede’, Francesco Regazzoni, Matteo Salvador, Toni Lassila, Antonio Frontera, Paolo Della Bella, Luca Rosario Limite and Natalia A. Trayanova. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of Computational Physics.
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.