Luana Ruiz
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Information Systems
- Electrical and Electronic Engineering
- Co-authors
- Alejandro RibeiroFernando GamaZhiyang WangAntonio G. MarquésLuiz F. O. ChamonA. BalaguerA. MarçalJ. A. Recio
- Topics
- Advanced Graph Neural Networks (19 papers)Stochastic Gradient Optimization Techniques (4 papers)Topological and Geometric Data Analysis (4 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Signal ProcessingNeural Information Processing Systems
- Partner nations
- United StatesSpain
In The Last Decade
Luana Ruiz
23 papers receiving 244 citations
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 137
- Computer Vision and Pattern Recognition 63
- Computer Networks and Communications 39
- Information Systems 39
- Electrical and Electronic Engineering 32
Countries citing papers authored by Luana Ruiz
This map shows the geographic impact of Luana Ruiz'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 Luana Ruiz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luana Ruiz more than expected).
Fields of papers citing papers by Luana Ruiz
This network shows the impact of papers produced by Luana Ruiz. 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 Luana Ruiz. The network helps show where Luana Ruiz may publish in the future.
Co-authorship network of co-authors of Luana Ruiz
This figure shows the co-authorship network connecting the top 25 collaborators of Luana Ruiz. A scholar is included among the top collaborators of Luana Ruiz 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 Luana Ruiz. Luana Ruiz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 10 | |
| 8 | 5 | |
| 9 | 6 | |
| 10 | 5 | |
| 11 | 6 | |
| 12 | 10 | |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 7 | |
| 16 | Graphon Neural Networks and the Transferability of Graph Neural Networks | 4 |
| 17 | 112 | |
| 18 | 1 | |
| 19 | 35 | |
| 20 | Study of methods based on wavelets for texture classification of high resolution images. | 7 |
About Luana Ruiz
Luana Ruiz is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 25 papers that have together received 251 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (19 papers), Stochastic Gradient Optimization Techniques (4 papers) and Topological and Geometric Data Analysis (4 papers). The work is most often cited by research in Artificial Intelligence (137 citations), Computer Vision and Pattern Recognition (63 citations) and Statistical and Nonlinear Physics (23 citations). Luana Ruiz has collaborated with scholars based in United States and Spain. Frequent co-authors include Alejandro Ribeiro, Fernando Gama, Zhiyang Wang, Antonio G. Marqués, Luiz F. O. Chamon, A. Balaguer, A. Marçal, J. A. Recio, Mark Eisen and Txomin Hermosilla. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Signal Processing and Neural Information Processing Systems.
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.