Arnau Prat-Pèrez

40 total papers · 773 total citations
15 papers, 389 citations indexed

About

Arnau Prat-Pèrez is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Arnau Prat-Pèrez has authored 15 papers receiving a total of 389 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 7 papers in Statistical and Nonlinear Physics. Recurrent topics in Arnau Prat-Pèrez's work include Complex Network Analysis Techniques (7 papers), Graph Theory and Algorithms (6 papers) and Advanced Graph Neural Networks (6 papers). Arnau Prat-Pèrez is often cited by papers focused on Complex Network Analysis Techniques (7 papers), Graph Theory and Algorithms (6 papers) and Advanced Graph Neural Networks (6 papers). Arnau Prat-Pèrez collaborates with scholars based in Spain, United States and Netherlands. Arnau Prat-Pèrez's co-authors include David Domínguez-Sal, Josep-L. Larriba-Pey, Peter Boncz, Alexandru Iosup, Mihai Capotă, Tim Hegeman, Renzo Angles, Orri Erling, Sherif Sakr and Angela Bonifati and has published in prestigious journals such as ACM Computing Surveys, Proceedings of the VLDB Endowment and Electronics.

In The Last Decade

Arnau Prat-Pèrez

14 papers receiving 372 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Arnau Prat-Pèrez 192 187 174 168 97 15 389
Gilles Trédan 124 0.6× 212 1.1× 81 0.5× 132 0.8× 48 0.5× 30 445
Huiming Qu 55 0.3× 175 0.9× 138 0.8× 194 1.2× 141 1.5× 14 387
Yuntao Jia 153 0.8× 117 0.6× 144 0.8× 43 0.3× 71 0.7× 14 352
Gabriela Jacques-Silva 89 0.5× 147 0.8× 126 0.7× 306 1.8× 140 1.4× 21 444
Makoto Nakatsuji 152 0.8× 241 1.3× 129 0.7× 60 0.4× 135 1.4× 26 369
Steve Harenberg 38 0.2× 249 1.3× 247 1.4× 183 1.1× 41 0.4× 12 431
Isabelle Stanton 255 1.3× 143 0.8× 76 0.4× 184 1.1× 116 1.2× 7 383
You Peng 185 1.0× 127 0.7× 60 0.3× 177 1.1× 36 0.4× 22 340
Yatao Li 298 1.6× 209 1.1× 25 0.1× 169 1.0× 170 1.8× 18 429
Zhiping Zeng 189 1.0× 183 1.0× 84 0.5× 93 0.6× 103 1.1× 6 373

Countries citing papers authored by Arnau Prat-Pèrez

Since Specialization
Citations

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

Fields of papers citing papers by Arnau Prat-Pèrez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arnau Prat-Pèrez. 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 Arnau Prat-Pèrez. The network helps show where Arnau Prat-Pèrez may publish in the future.

Co-authorship network of co-authors of Arnau Prat-Pèrez

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

All Works

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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