Danilo Francati
Impact in
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- Cryptography and Data Security
- Privacy-Preserving Technologies in Data
- Stochastic Gradient Optimization Techniques
- Adversarial Robustness in Machine Learning
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- Blockchain Technology Applications and Security
- Cloud Data Security Solutions
Papers in
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- Cryptography and Data Security 5
- Privacy-Preserving Technologies in Data 3
- Stochastic Gradient Optimization Techniques 1
- Internet Traffic Analysis and Secure E-voting 1
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- Cloud Data Security Solutions 1
- Blockchain Technology Applications and Security 1
- Cryptography and Residue Arithmetic 1
- Co-authors
- Giuseppe Ateniese (3 shared papers)David Núñez (1 shared paper)Daniele Venturi (3 shared papers)Giulio Malavolta (1 shared paper)
- Journals
- Journal of Cryptology (2 papers)Designs Codes and Cryptography (1 paper)Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security (1 paper)IRIS Research product catalog (Sapienza University of Rome) (1 paper)
- Partner nations
- ItalyUnited StatesDenmark
In The Last Decade
Danilo Francati
3 papers receiving 109 citations
Peers
Comparison fields: 5 of 23
- Artificial Intelligence 90
- Information Systems 34
- Computer Networks and Communications 17
- Health Informatics 1
- Computer Science Applications 3
Countries citing papers authored by Danilo Francati
This map shows the geographic impact of Danilo Francati'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 Danilo Francati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danilo Francati more than expected).
Fields of papers citing papers by Danilo Francati
This network shows the impact of papers produced by Danilo Francati. 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 Danilo Francati. The network helps show where Danilo Francati may publish in the future.
Co-authors
The 4 scholars most cited alongside Danilo Francati, 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 | 2022 | 59 | |
| 2 | 2021 | 29 | |
| 3 | 2021 | 21 | |
| 4 | 2024 | 0 | |
| 5 | 2025 | 0 |
About Danilo Francati
Danilo Francati is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Infectious Diseases, having authored 5 papers that have together received 109 indexed citations. Recurring topics across this work include Cryptography and Data Security (5 papers), Privacy-Preserving Technologies in Data (3 papers), Complexity and Algorithms in Graphs (1 paper), Cloud Data Security Solutions (1 paper), Stochastic Gradient Optimization Techniques (1 paper), Internet Traffic Analysis and Secure E-voting (1 paper), Blockchain Technology Applications and Security (1 paper) and Cryptography and Residue Arithmetic (1 paper). The work is most often cited by research in Artificial Intelligence (90 citations), Information Systems (34 citations), Computer Networks and Communications (17 citations), Health Informatics (1 citation) and Computer Science Applications (3 citations). Danilo Francati has collaborated with scholars based in Italy, United States and Denmark. Frequent co-authors include Giuseppe Ateniese, David Núñez, Daniele Venturi and Giulio Malavolta. Their work appears in journals such as Journal of Cryptology, Designs Codes and Cryptography, Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security and IRIS Research product catalog (Sapienza University of Rome).
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.