Ferdinando Fioretto

1.3k total citations
49 papers, 484 citations indexed

About

Ferdinando Fioretto is a scholar working on Artificial Intelligence, Computer Networks and Communications and Management Science and Operations Research. According to data from OpenAlex, Ferdinando Fioretto has authored 49 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 15 papers in Computer Networks and Communications and 9 papers in Management Science and Operations Research. Recurrent topics in Ferdinando Fioretto's work include Privacy-Preserving Technologies in Data (19 papers), Constraint Satisfaction and Optimization (13 papers) and Mobile Crowdsensing and Crowdsourcing (6 papers). Ferdinando Fioretto is often cited by papers focused on Privacy-Preserving Technologies in Data (19 papers), Constraint Satisfaction and Optimization (13 papers) and Mobile Crowdsensing and Crowdsourcing (6 papers). Ferdinando Fioretto collaborates with scholars based in United States, Japan and Israel. Ferdinando Fioretto's 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 and has published in prestigious journals such as IEEE Transactions on Power Systems, Artificial Intelligence and Electric Power Systems Research.

In The Last Decade

Ferdinando Fioretto

47 papers receiving 475 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ferdinando Fioretto United States 12 220 169 86 85 76 49 484
Tal Grinshpoun Israel 11 85 0.4× 164 1.0× 29 0.3× 88 1.0× 88 1.2× 47 337
James Pita United States 11 103 0.5× 145 0.9× 21 0.2× 130 1.5× 19 0.3× 19 630
Nico Piatkowski Germany 12 185 0.8× 111 0.7× 63 0.7× 18 0.2× 80 1.1× 48 486
Mohammad Ahsan Chishti India 15 147 0.7× 287 1.7× 88 1.0× 13 0.2× 64 0.8× 59 565
Gianlorenzo D’Angelo Italy 14 80 0.4× 326 1.9× 45 0.5× 48 0.6× 61 0.8× 64 694
Yongjie Yang Germany 9 98 0.4× 71 0.4× 68 0.8× 72 0.8× 8 0.1× 51 361
Haimonti Dutta United States 9 161 0.7× 71 0.4× 118 1.4× 22 0.3× 50 0.7× 21 375
Branislav Bošanský Czechia 14 188 0.9× 185 1.1× 12 0.1× 106 1.2× 64 0.8× 47 485
Teng Hu China 11 227 1.0× 155 0.9× 47 0.5× 40 0.5× 111 1.5× 37 483
Eric A. Hansen United States 9 348 1.6× 183 1.1× 14 0.2× 122 1.4× 21 0.3× 19 496

Countries citing papers authored by Ferdinando Fioretto

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Kailkhura, Bhavya, et al.. (2025). Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion. 12042–12059. 2 indexed citations
2.
Guns, Tias, et al.. (2024). Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities. Journal of Artificial Intelligence Research. 80. 1623–1701. 28 indexed citations
3.
Tran, Cuong Dinh, Kèyù Zhü, Ferdinando Fioretto, & Pascal Van Hentenryck. (2023). SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles. 501–509. 4 indexed citations
4.
Baker, Kyri, et al.. (2023). Gradient-enhanced physics-informed neural networks for power systems operational support. Electric Power Systems Research. 223. 109551–109551. 19 indexed citations
5.
Tran, Cuong & Ferdinando Fioretto. (2023). On the Fairness Impacts of Private Ensembles Models. 510–518. 2 indexed citations
6.
Fioretto, Ferdinando, et al.. (2023). Differentiable Model Selection for Ensemble Learning. 1954–1962. 3 indexed citations
7.
Tran, Cuong Dinh, et al.. (2021). Privacy-Preserving and Accountable Multi-agent Learning. Autonomous Agents and Multi-Agent Systems. 1605–1606. 2 indexed citations
8.
Tran, Cuong Dinh, et al.. (2021). Differentially Private Empirical Risk Minimization under the Fairness Lens. Neural Information Processing Systems. 34. 10 indexed citations
9.
Tran, Cuong Dinh, Ferdinando Fioretto, Pascal Van Hentenryck, & Zhiyan Yao. (2021). Decision Making with Differential Privacy under a Fairness Lens. 560–566. 21 indexed citations
10.
Fioretto, Ferdinando & Pascal Van Hentenryck. (2019). Privacy-Preserving Federated Data Sharing. Adaptive Agents and Multi-Agents Systems. 638–646. 6 indexed citations
11.
Fioretto, Ferdinando, et al.. (2018). Constrained-Based Differential Privacy for Mobility Services. Adaptive Agents and Multi-Agents Systems. 1405–1413. 3 indexed citations
12.
Fioretto, Ferdinando, Hong Xu, Sven Koenig, & T. K. Satish Kumar. (2018). Constraint Composite Graph-Based Lifted Message Passing for Distributed Constraint Optimization Problems..
13.
Fioretto, Ferdinando, William Yeoh, & Enrico Pontelli. (2017). A Multiagent System Approach to Scheduling Devices in Smart Homes. National Conference on Artificial Intelligence. 981–989. 12 indexed citations
14.
Hou, Ping, et al.. (2017). Infinite-Horizon Proactive Dynamic DCOPs. Adaptive Agents and Multi-Agents Systems. 212–220. 7 indexed citations
15.
Fioretto, Ferdinando, William Yeoh, & Enrico Pontelli. (2017). A Multiagent System Approach to Scheduling Devices in Smart Homes. Adaptive Agents and Multi-Agents Systems. 981–989. 29 indexed citations
16.
Fioretto, Ferdinando, et al.. (2016). Proactive Dynamic Distributed Constraint Optimization. Adaptive Agents and Multi-Agents Systems. 597–605. 12 indexed citations
17.
Fioretto, Ferdinando, et al.. (2016). ER-DCOPs: A Framework for Distributed Constraint Optimization with Uncertainty in Constraint Utilities. Adaptive Agents and Multi-Agents Systems. 606–614. 5 indexed citations
18.
Fioretto, Ferdinando, William Yeoh, & Enrico Pontelli. (2016). Multi-Variable Agent decomposition for DCOPs. National Conference on Artificial Intelligence. 2480–2486. 10 indexed citations
19.
Fioretto, Ferdinando, William Yeoh, & Enrico Pontelli. (2015). Multi-Variable Agents Decomposition for DCOPs to Exploit Multi-Level Parallelism. Adaptive Agents and Multi-Agents Systems. 1823–1824. 1 indexed citations
20.
Fioretto, Ferdinando, et al.. (2014). GD-GIBBS: a GPU-based sampling algorithm for solving distributed constraint optimization problems. Adaptive Agents and Multi-Agents Systems. 1339–1340. 5 indexed citations

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.

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2026