Ricardo Cerri
- Artificial Intelligence top 2%
- Molecular Biology
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Computational Theory and Mathematics top 5%
- Co-authors
- André C. P. L. F. de CarvalhoRodrigo C. BarrosJônatas WehrmannRafael Gomes MantovaniSylvio BarbonYaochu JinTomáš HorváthJoaquin Vanschoren
- Topics
- Text and Document Classification Technologies (33 papers)Machine Learning in Bioinformatics (20 papers)Machine Learning and Data Classification (17 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionComputational Theory and Mathematics
- Partner nations
- BrazilUnited KingdomBelgium
In The Last Decade
Ricardo Cerri
62 papers receiving 824 citations
Peers
Comparison fields: 5 of 127
- Artificial Intelligence 494
- Molecular Biology 225
- Computer Vision and Pattern Recognition 148
- Information Systems 120
- Computational Theory and Mathematics 87
Countries citing papers authored by Ricardo Cerri
This map shows the geographic impact of Ricardo Cerri'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 Ricardo Cerri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ricardo Cerri more than expected).
Fields of papers citing papers by Ricardo Cerri
This network shows the impact of papers produced by Ricardo Cerri. 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 Ricardo Cerri. The network helps show where Ricardo Cerri may publish in the future.
Co-authorship network of co-authors of Ricardo Cerri
This figure shows the co-authorship network connecting the top 25 collaborators of Ricardo Cerri. A scholar is included among the top collaborators of Ricardo Cerri 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 Ricardo Cerri. Ricardo Cerri 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 | 0 | |
| 3 | 0 | |
| 4 | 20 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 8 | |
| 12 | 1 | |
| 13 | Hierarchical and Non-Hierarchical Classification of Transposable Elements with a Genetic Algorithm | 2 |
| 14 | 24 | |
| 15 | Hierarchical Multi-Label Classification Networks | 80 |
| 16 | 28 | |
| 17 | Hyper-Parameter Tuning of a Decision Tree Induction Algorithm | 1 |
| 18 | Annotating transposable elements in the genome using relational decision tree ensembles | 3 |
| 19 | 85 | |
| 20 | 15 |
About Ricardo Cerri
Ricardo Cerri is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 69 papers that have together received 844 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (33 papers), Machine Learning in Bioinformatics (20 papers) and Machine Learning and Data Classification (17 papers). The work is most often cited by research in Artificial Intelligence (494 citations), Computer Vision and Pattern Recognition (148 citations) and Computational Theory and Mathematics (87 citations). Ricardo Cerri has collaborated with scholars based in Brazil, United Kingdom and Belgium. Frequent co-authors include André C. P. L. F. de Carvalho, Rodrigo C. Barros, Jônatas Wehrmann, Rafael Gomes Mantovani, Sylvio Barbon, Yaochu Jin, Tomáš Horváth, Joaquin Vanschoren, Alex A. Freitas and Saulo Martiello Mastelini. Their work appears in journals such as Bioinformatics, Expert Systems with Applications and Gene.
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.