Luca Becchetti

2.8k total citations
60 papers, 1.5k citations indexed

About

Luca Becchetti is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Luca Becchetti has authored 60 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Computer Networks and Communications, 16 papers in Statistical and Nonlinear Physics and 13 papers in Artificial Intelligence. Recurrent topics in Luca Becchetti's work include Optimization and Search Problems (14 papers), Complex Network Analysis Techniques (14 papers) and Caching and Content Delivery (11 papers). Luca Becchetti is often cited by papers focused on Optimization and Search Problems (14 papers), Complex Network Analysis Techniques (14 papers) and Caching and Content Delivery (11 papers). Luca Becchetti collaborates with scholars based in Italy, United States and Spain. Luca Becchetti's co-authors include Carlos Castillo, Stefano Leonardi, Aristides Gionis, Aris Anagnostopoulos, Paolo Boldi, Debora Donato, Ricardo Baeza‐Yates, Massimo Santini, Sebastiano Vigna and Alberto Marchetti-Spaccamela and has published in prestigious journals such as Bioinformatics, IEEE Communications Magazine and Information Sciences.

In The Last Decade

Luca Becchetti

56 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luca Becchetti Italy 18 597 525 517 410 184 60 1.5k
Sreenivas Gollapudi United States 19 811 1.4× 748 1.4× 433 0.8× 307 0.7× 105 0.6× 76 1.9k
Ronny Lempel Israel 21 1.3k 2.1× 725 1.4× 424 0.8× 421 1.0× 55 0.3× 52 1.9k
S. P. Rajagopalan India 15 473 0.8× 405 0.8× 361 0.7× 415 1.0× 21 0.1× 48 1.3k
Ali Dasdan United States 17 512 0.9× 274 0.5× 699 1.4× 106 0.3× 32 0.2× 48 1.5k
Feida Zhu Singapore 28 1.1k 1.8× 1.5k 2.9× 405 0.8× 731 1.8× 264 1.4× 103 2.5k
Adriana Iamnitchi United States 21 940 1.6× 377 0.7× 2.3k 4.4× 384 0.9× 89 0.5× 82 2.9k
William Yurcik United States 23 531 0.9× 513 1.0× 933 1.8× 230 0.6× 155 0.8× 117 1.7k
Nívio Ziviani Brazil 24 1.1k 1.8× 1.1k 2.1× 527 1.0× 113 0.3× 54 0.3× 115 2.0k
Kyomin Jung South Korea 18 556 0.9× 925 1.8× 294 0.6× 747 1.8× 40 0.2× 114 2.1k

Countries citing papers authored by Luca Becchetti

Since Specialization
Citations

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

Fields of papers citing papers by Luca Becchetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luca Becchetti

This figure shows the co-authorship network connecting the top 25 collaborators of Luca Becchetti. A scholar is included among the top collaborators of Luca Becchetti 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 Luca Becchetti. Luca Becchetti 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.
Becchetti, Luca, et al.. (2025). Approximate 2-hop Neighborhoods on Incremental Graphs: An Efficient Lazy Approach. Proceedings of the VLDB Endowment. 18(11). 3937–3950.
2.
Becchetti, Luca, et al.. (2023). On the Role of Memory in Robust Opinion Dynamics. Cineca Institutional Research Information System (Tor Vergata University). 29–37. 3 indexed citations
3.
Becchetti, Luca, et al.. (2020). Step-by-step community detection in volume-regular graphs. Cineca Institutional Research Information System (Tor Vergata University). 3 indexed citations
4.
Anagnostopoulos, Aris, et al.. (2020). Spectral Relaxations and Fair Densest Subgraphs. IRIS Research product catalog (Sapienza University of Rome). 35–44. 12 indexed citations
5.
Becchetti, Luca, Andrea Clementi, Emanuele Natale, et al.. (2017). Friend or Foe? Population Protocols can perform Community Detection. arXiv (Cornell University). 1 indexed citations
6.
Becchetti, Luca, Andrea Clementi, Emanuele Natale, Francesco Pasquale, & Luca Trevisan. (2017). Find your place: simple distributed algorithms for community detection. Symposium on Discrete Algorithms. 940–959. 4 indexed citations
7.
Becchetti, Luca, Andrea Clementi, Emanuele Natale, et al.. (2016). Simple dynamics for plurality consensus. Distributed Computing. 30(4). 293–306. 17 indexed citations
8.
Becchetti, Luca, Andrea Clementi, Emanuele Natale, et al.. (2013). Simple Dynamics for Majority Consensus. arXiv (Cornell University). 1 indexed citations
9.
Becchetti, Luca, Andrea Clementi, Francesco Pasquale, et al.. (2013). Flooding Time in Opportunistic Networks under Power Law and Exponential Intercontact Times. IEEE Transactions on Parallel and Distributed Systems. 25(9). 2297–2306. 15 indexed citations
10.
Becchetti, Luca. (2012). Compact data structures: data streaming.
11.
Becchetti, Luca, Andrea Clementi, Francesco Pasquale, et al.. (2011). Information Spreading in Opportunistic Networks is Fast. arXiv (Cornell University). 244(Pt 1). 151–159. 3 indexed citations
12.
Becchetti, Luca, et al.. (2009). Latency-constrained aggregation in sensor networks. ACM Transactions on Algorithms. 6(1). 1–20. 24 indexed citations
13.
Becchetti, Luca, Stefano Leonardi, Alberto Marchetti-Spaccamela, & Kirk Pruhs. (2006). Online weighted flow time and deadline scheduling. Journal of Discrete Algorithms. 4(3). 339–352. 35 indexed citations
14.
Becchetti, Luca, et al.. (2006). A Comparison of Sampling Techniques for Web Graph Characterization. IRIS Research product catalog (Sapienza University of Rome). 38 indexed citations
15.
Becchetti, Luca, Jochen Könemann, Stefano Leonardi, & Martin Pál. (2005). Sharing the cost more efficiently: improved approximation for multicommodity rent-or-buy. Symposium on Discrete Algorithms. 375–384. 8 indexed citations
16.
Becchetti, Luca, Stefano Leonardi, Alberto Marchetti-Spaccamela, & Kirk Pruhs. (2004). Semi-clairvoyant scheduling. Theoretical Computer Science. 324(2-3). 325–335. 3 indexed citations
17.
Becchetti, Luca, Stefano Leonardi, & S. Muthukrishnan. (2003). Average stretch without migration. Journal of Computer and System Sciences. 68(1). 80–95. 6 indexed citations
18.
Becchetti, Luca, Suhas Diggavi, Stefano Leonardi, et al.. (2002). Parallel scheduling problems in next generation wireless networks. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 238–247. 9 indexed citations
19.
Becchetti, Luca, et al.. (2002). Approximation algorithms for routing and call scheduling in all-optical chains and rings. Theoretical Computer Science. 287(2). 429–448. 4 indexed citations
20.
Becchetti, Luca, Stefano Leonardi, & S. Muthukrishnan. (2000). Scheduling to minimize average stretch without migration. Symposium on Discrete Algorithms. 548–557. 27 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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