Andrés Aragoneses
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Economics and Econometrics top 10%
- Co-authors
- Cristina MasollerM. C. TorrentArjendu K. PattanayakDaniel J. GauthierJ. BelanaM. MudarraLaura C. CarpiDmitry V. Churkin
- Topics
- Nonlinear Dynamics and Pattern Formation (12 papers)Chaos control and synchronization (9 papers)Neural Networks and Reservoir Computing (8 papers)
- Cited by
- Statistical and Nonlinear PhysicsAcoustics and UltrasonicsComputer Networks and Communications
- Journals
- Physical Review LettersSHILAP Revista de lepidopterologíaScientific Reports
- Partner nations
- United StatesSpainBrazil
In The Last Decade
Andrés Aragoneses
32 papers receiving 303 citations
Peers
Comparison fields: 5 of 60
- Statistical and Nonlinear Physics 110
- Artificial Intelligence 104
- Computer Networks and Communications 95
- Electrical and Electronic Engineering 87
- Economics and Econometrics 72
Countries citing papers authored by Andrés Aragoneses
This map shows the geographic impact of Andrés Aragoneses'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 Andrés Aragoneses with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrés Aragoneses more than expected).
Fields of papers citing papers by Andrés Aragoneses
This network shows the impact of papers produced by Andrés Aragoneses. 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 Andrés Aragoneses. The network helps show where Andrés Aragoneses may publish in the future.
Co-authorship network of co-authors of Andrés Aragoneses
This figure shows the co-authorship network connecting the top 25 collaborators of Andrés Aragoneses. A scholar is included among the top collaborators of Andrés Aragoneses 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 Andrés Aragoneses. Andrés Aragoneses is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | 8 | |
| 9 | 7 | |
| 10 | 12 | |
| 11 | 14 | |
| 12 | 10 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 43 | |
| 16 | 45 | |
| 17 | 3 | |
| 18 | 26 | |
| 19 | 8 | |
| 20 | 2 |
About Andrés Aragoneses
Andrés Aragoneses is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Artificial Intelligence, having authored 33 papers that have together received 311 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (12 papers), Chaos control and synchronization (9 papers) and Neural Networks and Reservoir Computing (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (110 citations), Acoustics and Ultrasonics (5 citations) and Computer Networks and Communications (95 citations). Andrés Aragoneses has collaborated with scholars based in United States, Spain and Brazil. Frequent co-authors include Cristina Masoller, M. C. Torrent, Arjendu K. Pattanayak, Daniel J. Gauthier, J. Belana, M. Mudarra, Laura C. Carpi, Dmitry V. Churkin, Nikita Tarasov and Sergei K. Turitsyn. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Scientific Reports.
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.