Arnau Prat-Pèrez
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 5%
- Information Systems top 10%
- Co-authors
- David Domínguez-SalJosep-L. Larriba-PeyPeter BonczMihai CapotăAlexandru IosupTim HegemanOrri ErlingRenzo Angles
- Topics
- Complex Network Analysis Techniques (7 papers)Graph Theory and Algorithms (6 papers)Advanced Graph Neural Networks (6 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Vision and Pattern RecognitionComputer Networks and Communications
- Partner nations
- SpainUnited StatesNetherlands
In The Last Decade
Arnau Prat-Pèrez
14 papers receiving 376 citations
Peers
Comparison fields: 5 of 40
- Computer Vision and Pattern Recognition 196
- Artificial Intelligence 190
- Statistical and Nonlinear Physics 176
- Computer Networks and Communications 168
- Information Systems 97
Countries citing papers authored by Arnau Prat-Pèrez
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 24 | |
| 3 | 10 | |
| 4 | 14 | |
| 5 | 9 | |
| 6 | 0 | |
| 7 | 82 | |
| 8 | 26 | |
| 9 | 4 | |
| 10 | 10 | |
| 11 | 41 | |
| 12 | 8 | |
| 13 | 93 | |
| 14 | 31 | |
| 15 | 38 |
About Arnau Prat-Pèrez
Arnau Prat-Pèrez is a scholar working on Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 15 papers that have together received 393 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Graph Theory and Algorithms (6 papers) and Advanced Graph Neural Networks (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (176 citations), Computer Vision and Pattern Recognition (196 citations) and Computer Networks and Communications (168 citations). Arnau Prat-Pèrez has collaborated with scholars based in Spain, United States and Netherlands. Frequent co-authors include David Domínguez-Sal, Josep-L. Larriba-Pey, Peter Boncz, Mihai Capotă, Alexandru Iosup, Tim Hegeman, Orri Erling, Renzo Angles, Michael Anderson and Narayanan Sundaram. Their work appears in journals such as ACM Computing Surveys, Proceedings of the VLDB Endowment and Electronics.
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.