Rubén Cuevas

1.9k total citations
94 papers, 1.1k citations indexed

About

Rubén Cuevas is a scholar working on Computer Networks and Communications, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Rubén Cuevas has authored 94 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Computer Networks and Communications, 32 papers in Sociology and Political Science and 21 papers in Artificial Intelligence. Recurrent topics in Rubén Cuevas's work include Caching and Content Delivery (34 papers), Peer-to-Peer Network Technologies (31 papers) and Internet Traffic Analysis and Secure E-voting (12 papers). Rubén Cuevas is often cited by papers focused on Caching and Content Delivery (34 papers), Peer-to-Peer Network Technologies (31 papers) and Internet Traffic Analysis and Secure E-voting (12 papers). Rubén Cuevas collaborates with scholars based in Spain, United Kingdom and France. Rubén Cuevas's co-authors include √Ångel Cuevas, Andreas Mauthe, Nishanth Sastry, Gareth Tyson, Ivica Rimac, Arturo Azcorra, Carmen Guerrero, Nikolaos Laoutaris, Roberto González and Albert Banchs and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.

In The Last Decade

Rubén Cuevas

88 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rubén Cuevas Spain	19	605	254	239	201	136	94	1.1k
√Ångel Cuevas Spain	15	316 0.5×	219 0.9×	166 0.7×	159 0.8×	171 1.3×	75	749
Vijay Erramilli Spain	16	839 1.4×	266 1.0×	212 0.9×	228 1.1×	195 1.4×	25	1.3k
Adam Wierzbicki Poland	17	347 0.6×	243 1.0×	274 1.1×	231 1.1×	49 0.4×	88	1.0k
Jari Veijalainen Finland	17	326 0.5×	202 0.8×	286 1.2×	569 2.8×	76 0.6×	75	1.1k
Simon Caton Ireland	14	352 0.6×	144 0.6×	303 1.3×	621 3.1×	45 0.3×	61	1.3k
Paraskevi Fragopoulou Greece	13	364 0.6×	151 0.6×	289 1.2×	327 1.6×	72 0.5×	65	886
Arjuna Sathiaseelan United Kingdom	18	741 1.2×	143 0.6×	118 0.5×	229 1.1×	242 1.8×	82	1.3k
Craig E. Wills United States	23	864 1.4×	722 2.8×	678 2.8×	693 3.4×	118 0.9×	80	2.0k
Joseph G. Davis Australia	17	183 0.3×	116 0.5×	229 1.0×	399 2.0×	64 0.5×	76	959
Wanita Sherchan Australia	11	279 0.5×	381 1.5×	307 1.3×	329 1.6×	40 0.3×	18	785

Countries citing papers authored by Rubén Cuevas

Since Specialization

Citations

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

Fields of papers citing papers by Rubén Cuevas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rubén Cuevas

This figure shows the co-authorship network connecting the top 25 collaborators of Rubén Cuevas. A scholar is included among the top collaborators of Rubén Cuevas 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 Rubén Cuevas. Rubén Cuevas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lassmann, Andrea, et al.. (2025). Global spillovers of taxation in the online advertising market. Theory and evidence from facebook. European Economic Review. 172. 104935–104935.

Redoano, Michela, et al.. (2025). Politics in the facebook era. Evidence from the 2016 US presidential elections. European Journal of Political Economy. 87. 102641–102641. 2 indexed citations

Cuevas, √Ångel, et al.. (2024). Overprofiling Analysis on Major Internet Players. Proceedings on Privacy Enhancing Technologies. 2024(4). 929–946.

Cuevas, Rubén, √Ångel Cuevas, David Klein, et al.. (2024). FP-tracer: Fine-grained Browser Fingerprinting Detection via Taint-tracking and Entropy-based Thresholds. Proceedings on Privacy Enhancing Technologies. 2024(3). 540–560.

Redoano, Michela, et al.. (2023). Politics in the Facebook Era. Evidence from The 2016 Us Presidential Elections. SSRN Electronic Journal. 1 indexed citations

Cuevas, Rubén, et al.. (2023). CarbonTag: A Browser-Based Method for Approximating Energy Consumption of Online Ads. IEEE Transactions on Sustainable Computing. 8(4). 739–750. 1 indexed citations

Trevisan, Martino, Luca Vassio, Marco Mellia, et al.. (2022). A PIMS Development Kit for New Personal Data Platforms. IEEE Internet Computing. 26(3). 79–84. 5 indexed citations

Cuevas, √Ångel, et al.. (2022). Estimating ideology and polarization in European countries using Facebook data. EPJ Data Science. 11(1). 56–56. 3 indexed citations

Cuevas, √Ångel, et al.. (2021). How resilient is the open web to the COVID-19 pandemic?. Telematics and Informatics. 64. 101692–101692. 1 indexed citations

10.

Cuevas, √Ångel, Rubén Cuevas, Klaus Desmet, & Ignacio Ortuño‐Ortín. (2021). The Gender Gap in Preferences: Evidence from 45,397 Facebook Interests. SSRN Electronic Journal.

11.

Cuevas, Rubén, et al.. (2019). Measuring the Global Recursive DNS Infrastructure: A View From the Edge. IEEE Access. 7. 168020–168028. 9 indexed citations

12.

Kourtellis, Nicolas, et al.. (2019). Beyond content analysis: Detecting targeted ads via distributed counting. MPG.PuRe (Max Planck Society). 3 indexed citations

13.

Han, Xiao, Leye Wang, Reza Farahbakhsh, et al.. (2016). CSD: A multi-user similarity metric for community recommendation in online social networks. Expert Systems with Applications. 53. 14–26. 36 indexed citations

14.

Cuevas, √Ångel, et al.. (2016). Your Data in the Eyes of the Beholders: Design of a Unified Data Valuation Portal to Estimate Value of Personal Information from Market Perspective. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 701–705. 2 indexed citations

15.

Cuevas, Rubén, et al.. (2015). Quantifying the Economic and Cultural Biases of Social Media through Trending Topics. PLoS ONE. 10(7). e0134407–e0134407. 18 indexed citations

16.

Mikians, Jakub, et al.. (2014). Understanding Interest-based Behavioural Targeted Advertising.. arXiv (Cornell University). 2 indexed citations

17.

Xiao, Han, √Ångel Cuevas, Noël Crespi, Rubén Cuevas, & Xiaodi Huang. (2014). On exploiting social relationship and personal background for content discovery in P2P networks. Future Generation Computer Systems. 40. 17–29. 8 indexed citations

18.

Cuevas, Rubén, et al.. (2013). Connectivity properties of real BitTorrent swarms. KSII Transactions on Internet and Information Systems. 7(9). 2246–2267.

19.

Gómez, Alberto Gómez, et al.. (2008). New Metaheuristic for the Job Shop Scheduling Problem with PSO.. International Conference on Artificial Intelligence. 552–553. 1 indexed citations

20.

Cuevas, Rubén, Carmen Guerrero, √Ångel Cuevas, María Calderón, & Carlos J. Bernardos. (2007). P2P Based Architecture for Global Home Agent Dynamic Discovery in IP Mobility. e-Archivo (Carlos III University of Madrid). 899–903. 13 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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