Francesca Scozzari
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 5%
- Software top 5%
- Information Systems
- Signal Processing
- Co-authors
- Roberto GiacobazziFrancesco RanzatoGianluca AmatoAnnamaria PorrecaMarta Di NicolaMaurizio PartonEnea ZaffanellaSalvador Cruz Rambaud
- Topics
- Logic, programming, and type systems (17 papers)Formal Methods in Verification (13 papers)Logic, Reasoning, and Knowledge (7 papers)
In The Last Decade
Francesca Scozzari
20 papers receiving 218 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 174
- Computational Theory and Mathematics 129
- Software 71
- Information Systems 39
- Signal Processing 33
Countries citing papers authored by Francesca Scozzari
This map shows the geographic impact of Francesca Scozzari'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 Francesca Scozzari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesca Scozzari more than expected).
Fields of papers citing papers by Francesca Scozzari
This network shows the impact of papers produced by Francesca Scozzari. 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 Francesca Scozzari. The network helps show where Francesca Scozzari may publish in the future.
Co-authorship network of co-authors of Francesca Scozzari
This figure shows the co-authorship network connecting the top 25 collaborators of Francesca Scozzari. A scholar is included among the top collaborators of Francesca Scozzari 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 Francesca Scozzari. Francesca Scozzari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 31 | |
| 4 | 1 | |
| 5 | 6 | |
| 6 | A Taxonomy of Program Analyses. | 1 |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 6 | |
| 10 | 2 | |
| 11 | 9 | |
| 12 | 8 | |
| 13 | 3 | |
| 14 | 4 | |
| 15 | On abstract unification for variable aliasing | 1 |
| 16 | 7 | |
| 17 | 5 | |
| 18 | 104 | |
| 19 | 24 | |
| 20 | The And-compositionality of CLP Computed Answer Constraints. | 1 |
About Francesca Scozzari
Francesca Scozzari is a scholar working on Software, Computational Theory and Mathematics and Artificial Intelligence, having authored 23 papers that have together received 229 indexed citations. Recurring topics across this work include Logic, programming, and type systems (17 papers), Formal Methods in Verification (13 papers) and Logic, Reasoning, and Knowledge (7 papers). The work is most often cited by research in Software (71 citations), Computational Theory and Mathematics (129 citations) and Artificial Intelligence (174 citations). Francesca Scozzari has collaborated with scholars based in Italy, Spain and France. Frequent co-authors include Roberto Giacobazzi, Francesco Ranzato, Gianluca Amato, Annamaria Porreca, Marta Di Nicola, Maurizio Parton, Enea Zaffanella, Salvador Cruz Rambaud, Maria Chiara Meo and Arcangelo Merla. Their work appears in journals such as BMC Public Health, Journal of the ACM and Theoretical Computer Science.
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.