Romano Scozzafava
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 2%
- Management Science and Operations Research top 2%
- General Decision Sciences top 5%
- Statistics and Probability top 5%
- Topics
- Bayesian Modeling and Causal Inference (21 papers)Logic, Reasoning, and Knowledge (13 papers)Multi-Criteria Decision Making (10 papers)
- Partner nations
- ItalyUnited KingdomFrance
In The Last Decade
Romano Scozzafava
37 papers receiving 577 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 526
- Computational Theory and Mathematics 235
- Management Science and Operations Research 235
- General Decision Sciences 80
- Statistics and Probability 67
Countries citing papers authored by Romano Scozzafava
This map shows the geographic impact of Romano Scozzafava'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 Romano Scozzafava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Romano Scozzafava more than expected).
Fields of papers citing papers by Romano Scozzafava
This network shows the impact of papers produced by Romano Scozzafava. 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 Romano Scozzafava. The network helps show where Romano Scozzafava may publish in the future.
Co-authorship network of co-authors of Romano Scozzafava
This figure shows the co-authorship network connecting the top 25 collaborators of Romano Scozzafava. A scholar is included among the top collaborators of Romano Scozzafava 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 Romano Scozzafava. Romano Scozzafava is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 12 | |
| 3 | Toward a general theory of conditional beliefs: Research Articles | 5 |
| 4 | 21 | |
| 5 | 4 | |
| 6 | Locally additive comparative probabilities. | 2 |
| 7 | 30 | |
| 8 | 3 | |
| 9 | Coherent Upper and Lower Bayesian Updating. | 11 |
| 10 | Null events and stochastical independence | 10 |
| 11 | 58 | |
| 12 | 1 | |
| 13 | 20 | |
| 14 | 15 | |
| 15 | Le probabilita condizionate coerenti nei sistemi esperti | 2 |
| 16 | 2 | |
| 17 | Non-standard methods | 1 |
| 18 | Atomic, nonatomic and continuous finitely additive measures: results and applications | 1 |
| 19 | Completa additività su opportune successioni di insiemi di una misura di probabilità semplicemente additiva e fortemente non atomica | 5 |
| 20 | 0 |
About Romano Scozzafava
Romano Scozzafava is a scholar working on General Decision Sciences, Management Science and Operations Research and Artificial Intelligence, having authored 41 papers that have together received 657 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (21 papers), Logic, Reasoning, and Knowledge (13 papers) and Multi-Criteria Decision Making (10 papers). The work is most often cited by research in General Decision Sciences (80 citations), Management Science and Operations Research (235 citations) and Artificial Intelligence (526 citations). Romano Scozzafava has collaborated with scholars based in Italy, United Kingdom and France. Frequent co-authors include Giulianella Coletti, Barbara Vantaggi, Angelo Gilio, Didier Dubois and Antonio Di Nola. Their work appears in journals such as Information Sciences, Fuzzy Sets and Systems and Computational Statistics & Data Analysis.
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.