Ferdinando Fioretto
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Electrical and Electronic Engineering
- Management Science and Operations Research top 10%
- Signal Processing top 10%
- Co-authors
- Pascal Van HentenryckWilliam YeohEnrico PontelliCuong Dinh TranKèyù ZhüTerrence W. K. MakKyri BakerZhiyan Yao
- Topics
- Privacy-Preserving Technologies in Data (19 papers)Constraint Satisfaction and Optimization (13 papers)Mobile Crowdsensing and Crowdsourcing (6 papers)
- Partner nations
- United StatesJapanIsrael
In The Last Decade
Ferdinando Fioretto
47 papers receiving 475 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 220
- Computer Networks and Communications 169
- Electrical and Electronic Engineering 86
- Management Science and Operations Research 85
- Signal Processing 76
Countries citing papers authored by Ferdinando Fioretto
This map shows the geographic impact of Ferdinando Fioretto'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 Ferdinando Fioretto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ferdinando Fioretto more than expected).
Fields of papers citing papers by Ferdinando Fioretto
This network shows the impact of papers produced by Ferdinando Fioretto. 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 Ferdinando Fioretto. The network helps show where Ferdinando Fioretto may publish in the future.
Co-authorship network of co-authors of Ferdinando Fioretto
This figure shows the co-authorship network connecting the top 25 collaborators of Ferdinando Fioretto. A scholar is included among the top collaborators of Ferdinando Fioretto 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 Ferdinando Fioretto. Ferdinando Fioretto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 28 | |
| 3 | 4 | |
| 4 | 19 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | Differentially Private Empirical Risk Minimization under the Fairness Lens | 10 |
| 9 | 21 | |
| 10 | 6 | |
| 11 | 3 | |
| 12 | Constraint Composite Graph-Based Lifted Message Passing for Distributed Constraint Optimization Problems. | 0 |
| 13 | 12 | |
| 14 | 7 | |
| 15 | 29 | |
| 16 | 12 | |
| 17 | 5 | |
| 18 | Multi-Variable Agent decomposition for DCOPs | 10 |
| 19 | 1 | |
| 20 | 5 |
About Ferdinando Fioretto
Ferdinando Fioretto is a scholar working on Computer Science Applications, Artificial Intelligence and Management Science and Operations Research, having authored 49 papers that have together received 484 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (19 papers), Constraint Satisfaction and Optimization (13 papers) and Mobile Crowdsensing and Crowdsourcing (6 papers). The work is most often cited by research in Computer Networks and Communications (169 citations), Signal Processing (76 citations) and Artificial Intelligence (220 citations). Ferdinando Fioretto has collaborated with scholars based in United States, Japan and Israel. Frequent co-authors include Pascal Van Hentenryck, William Yeoh, Enrico Pontelli, Cuong Dinh Tran, Kèyù Zhü, Terrence W. K. Mak, Kyri Baker, Zhiyan Yao, Tias Guns and Makoto Yokoo. Their work appears in journals such as IEEE Transactions on Power Systems, Artificial Intelligence and Electric Power Systems Research.
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.