Leonardo G. Brunnet
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 10%
- Cognitive Neuroscience
- Condensed Matter Physics top 10%
- Biomedical Engineering
- Co-authors
- Hugues ChatéRita M. C. de AlmeidaGilberto L. ThomasJulio M. BelmontePaul MannevilleSilvia De MonteEverton J. AgnesSebastián Gonçalves
- Topics
- Nonlinear Dynamics and Pattern Formation (11 papers)Neural dynamics and brain function (9 papers)Micro and Nano Robotics (8 papers)
In The Last Decade
Leonardo G. Brunnet
33 papers receiving 383 citations
Peers
Comparison fields: 5 of 84
- Statistical and Nonlinear Physics 163
- Computer Networks and Communications 146
- Cognitive Neuroscience 99
- Condensed Matter Physics 97
- Biomedical Engineering 74
Countries citing papers authored by Leonardo G. Brunnet
This map shows the geographic impact of Leonardo G. Brunnet'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 Leonardo G. Brunnet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonardo G. Brunnet more than expected).
Fields of papers citing papers by Leonardo G. Brunnet
This network shows the impact of papers produced by Leonardo G. Brunnet. 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 Leonardo G. Brunnet. The network helps show where Leonardo G. Brunnet may publish in the future.
Co-authorship network of co-authors of Leonardo G. Brunnet
This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo G. Brunnet. A scholar is included among the top collaborators of Leonardo G. Brunnet 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 Leonardo G. Brunnet. Leonardo G. Brunnet 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 | 4 | |
| 3 | 14 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 19 | |
| 7 | 10 | |
| 8 | 9 | |
| 9 | 24 | |
| 10 | 6 | |
| 11 | 16 | |
| 12 | 1 | |
| 13 | 13 | |
| 14 | 92 | |
| 15 | 55 | |
| 16 | 13 | |
| 17 | 2 | |
| 18 | 3 | |
| 19 | 4 | |
| 20 | 8 |
About Leonardo G. Brunnet
Leonardo G. Brunnet is a scholar working on Condensed Matter Physics, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 35 papers that have together received 396 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (11 papers), Neural dynamics and brain function (9 papers) and Micro and Nano Robotics (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (163 citations), Condensed Matter Physics (97 citations) and Computer Networks and Communications (146 citations). Leonardo G. Brunnet has collaborated with scholars based in Brazil, France and Chile. Frequent co-authors include Hugues Chaté, Rita M. C. de Almeida, Gilberto L. Thomas, Julio M. Belmonte, Paul Manneville, Silvia De Monte, Everton J. Agnes, Sebastián Gonçalves, José Luiz Rybarczyk-Filho and Rodrigo Juliani Siqueira Dalmolin. Their work appears in journals such as Physical Review Letters, Nucleic Acids Research and PLoS ONE.
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.