Marco Fiore

6.2k total citations · 1 hit paper
155 papers, 4.1k citations indexed

About

Marco Fiore is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Transportation. According to data from OpenAlex, Marco Fiore has authored 155 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Computer Networks and Communications, 80 papers in Electrical and Electronic Engineering and 40 papers in Transportation. Recurrent topics in Marco Fiore's work include Opportunistic and Delay-Tolerant Networks (44 papers), Vehicular Ad Hoc Networks (VANETs) (43 papers) and Human Mobility and Location-Based Analysis (40 papers). Marco Fiore is often cited by papers focused on Opportunistic and Delay-Tolerant Networks (44 papers), Vehicular Ad Hoc Networks (VANETs) (43 papers) and Human Mobility and Location-Based Analysis (40 papers). Marco Fiore collaborates with scholars based in Spain, Italy and France. Marco Fiore's co-authors include Jérôme Härri, José M. Barceló-Ordinas, Fethi Filali, Christian Bonnet, Carla Fabiana Chiasserini, Oscar Trullols‐Cruces, Claudio Casetti, Marco Gramaglia, Sandesh Uppoor and Albert Banchs and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, IEEE Access and IEEE Journal on Selected Areas in Communications.

In The Last Decade

Marco Fiore

144 papers receiving 3.9k citations

Hit Papers

VanetMobiSim 2006 2026 2012 2019 2006 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. VanetMobiSim
    2006 347 citations Marco Fiore et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Fiore Spain 35 2.6k 2.5k 792 473 394 155 4.1k
Damla Turgut United States 27 2.8k 1.1× 1.3k 0.5× 322 0.4× 209 0.4× 255 0.6× 145 3.7k
Luciano Bononi Italy 28 1.9k 0.7× 1.4k 0.6× 209 0.3× 137 0.3× 140 0.4× 135 2.8k
Hannes Hartenstein Germany 43 7.5k 2.9× 7.1k 2.8× 346 0.4× 510 1.1× 273 0.7× 166 9.5k
Xiaoying Gan China 24 1.1k 0.4× 812 0.3× 260 0.3× 377 0.8× 193 0.5× 152 2.0k
Panos Papadimitratos Sweden 37 4.0k 1.5× 4.7k 1.9× 231 0.3× 1.9k 4.1× 173 0.4× 169 6.4k
Degan Zhang China 32 2.4k 0.9× 1.4k 0.6× 104 0.1× 473 1.0× 232 0.6× 76 3.4k
Fabrizio Granelli Italy 30 2.4k 0.9× 1.9k 0.8× 127 0.2× 273 0.6× 79 0.2× 259 3.5k
Kui Wu Canada 33 2.5k 0.9× 1.5k 0.6× 93 0.1× 803 1.7× 229 0.6× 212 4.1k
Ahmed Helmy United States 34 5.1k 1.9× 2.2k 0.9× 591 0.7× 233 0.5× 79 0.2× 193 5.7k
Kshirasagar Naik Canada 26 2.1k 0.8× 1.6k 0.6× 85 0.1× 351 0.7× 77 0.2× 184 3.0k

Countries citing papers authored by Marco Fiore

Since Specialization
Citations

This map shows the geographic impact of Marco Fiore'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 Marco Fiore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Fiore more than expected).

Fields of papers citing papers by Marco Fiore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco Fiore. 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 Marco Fiore. The network helps show where Marco Fiore may publish in the future.

Co-authorship network of co-authors of Marco Fiore

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Fiore. A scholar is included among the top collaborators of Marco Fiore 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 Marco Fiore. Marco Fiore 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.
Fiore, Marco, et al.. (2025). Real‐Time Encrypted Traffic Classification in Programmable Networks with P4 and Machine Learning. International Journal of Network Management. 35(1). 1 indexed citations
2.
Piazza, I. Di, et al.. (2025). Pre − test evaluation of a grid − spaced deformed fuel pin bundle. Nuclear Engineering and Design. 443. 114293–114293.
3.
Fiore, Marco, et al.. (2025). Empowering Wireless Network Applications with Deep Learning-Based Radio Propagation Models. IEEE Wireless Communications. 32(4). 124–131. 3 indexed citations
4.
Gucciardo, Michele, et al.. (2024). Jewel: Resource-Efficient Joint Packet and Flow Level Inference in Programmable Switches. Zenodo (CERN European Organization for Nuclear Research). 1631–1640. 11 indexed citations
5.
Fiore, Marco, et al.. (2024). Impact of Public Protests on Mobile Networks. 1–2.
6.
Fiore, Marco, et al.. (2024). Encrypted Traffic Classification at Line Rate in Programmable Switches with Machine Learning. Zenodo (CERN European Organization for Nuclear Research). 1–9. 5 indexed citations
7.
Gucciardo, Michele, et al.. (2024). Ultra-Low Latency User-Plane Cyberattack Detection in SDN-based Smart Grids. 676–682. 1 indexed citations
8.
Fiandrino, Claudio, et al.. (2024). Dissecting Advanced Time Series Forecasting Models with AICHRONOLENS. 1–2. 1 indexed citations
9.
Ziemlicki, Cezary, et al.. (2024). Characterizing 5G Adoption and its Impact on Network Traffic and Mobile Service Consumption. 1531–1540. 2 indexed citations
10.
Camelo, Miguel, Esteban Municio, Marco Gramaglia, et al.. (2024). Designing the Network Intelligence Stratum for 6G networks. Computer Networks. 254. 110780–110780. 3 indexed citations
11.
12.
Furno, Angelo, et al.. (2023). Adaptative generalisation over a value hierarchy for the k-anonymisation of Origin–Destination matrices. Transportation Research Part C Emerging Technologies. 154. 104236–104236. 3 indexed citations
13.
Brunström, Anna, et al.. (2023). Passive and Active Measurement. Lecture notes in computer science. 4 indexed citations
14.
Wassell, Ian, et al.. (2022). Deep-Learning-Based Multivariate Time-Series Classification for Indoor/Outdoor Detection. IEEE Internet of Things Journal. 9(23). 24529–24540. 11 indexed citations
15.
Chiaraviglio, Luca, Giuseppe Bianchi, Nicola Bléfari-Melazzi, & Marco Fiore. (2020). Will the Proliferation of 5G Base Stations Increase the Radio-Frequency 'Pollution'?. Cineca Institutional Research Information System (Tor Vergata University). 6 indexed citations
16.
Bega, Dario, Marco Gramaglia, Marco Fiore, Albert Banchs, & Xavier Costa‐Pérez. (2019). DeepCog: Optimizing Resource Provisioning in Network Slicing With AI-Based Capacity Forecasting. IEEE Journal on Selected Areas in Communications. 38(2). 361–376. 4 indexed citations
17.
Chen, Guangshuo, Aline Carneiro Viana, Marco Fiore, & Carlos Sarraute. (2019). Complete trajectory reconstruction from sparse mobile phone data. EPJ Data Science. 8(1). 41 indexed citations
18.
Bega, Dario, Marco Gramaglia, Marco Fiore, Albert Banchs, & Xavier Costa‐Pérez. (2019). α-OMC: Cost-Aware Deep Learning for Mobile Network Resource Orchestration. 4 indexed citations
19.
Chiaraviglio, Luca, et al.. (2018). Planning 5G Networks Under EMF Constraints: State of the Art and Vision. IEEE Access. 6. 51021–51037. 84 indexed citations
20.
Fiore, Marco & Catherine Rosenberg. (2012). Proceedings of the first workshop on Urban networking. 75(6). 433–4. 15 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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