Gustavo Batista
- Artificial Intelligence top 1%
- Signal Processing top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Economics and Econometrics top 10%
- Co-authors
- Maria Carolina MonardEamonn KeoghThanawin RakthanmanonQiang ZhuBilson CampanaBrandon WestoverAbdullah MueenJesin Zakaria
- Topics
- Anomaly Detection Techniques and Applications (13 papers)Imbalanced Data Classification Techniques (8 papers)Machine Learning and Data Classification (7 papers)
- Journals
- Expert Systems with ApplicationsNeurocomputingIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- BrazilAustraliaUnited States
In The Last Decade
Gustavo Batista
36 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Artificial Intelligence 1.0k
- Signal Processing 876
- Computer Vision and Pattern Recognition 269
- Information Systems 212
- Economics and Econometrics 151
Countries citing papers authored by Gustavo Batista
This map shows the geographic impact of Gustavo Batista'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 Gustavo Batista with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gustavo Batista more than expected).
Fields of papers citing papers by Gustavo Batista
This network shows the impact of papers produced by Gustavo Batista. 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 Gustavo Batista. The network helps show where Gustavo Batista may publish in the future.
Co-authorship network of co-authors of Gustavo Batista
This figure shows the co-authorship network connecting the top 25 collaborators of Gustavo Batista. A scholar is included among the top collaborators of Gustavo Batista 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 Gustavo Batista. Gustavo Batista 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 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 0 | |
| 10 | 22 | |
| 11 | 102 | |
| 12 | 52 | |
| 13 | 101 | |
| 14 | 145 | |
| 15 | 11 | |
| 16 | 31 | |
| 17 | 9 | |
| 18 | 30 | |
| 19 | An analysis of four missing data treatment methods for supervised learningbreakdown → | 573 |
| 20 | 2 |
About Gustavo Batista
Gustavo Batista is a scholar working on Artificial Intelligence, Signal Processing and Ecological Modeling, having authored 46 papers that have together received 2.1k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (13 papers), Imbalanced Data Classification Techniques (8 papers) and Machine Learning and Data Classification (7 papers). The work is most often cited by research in Signal Processing (876 citations), Artificial Intelligence (1.0k citations) and Developmental Biology (36 citations). Gustavo Batista has collaborated with scholars based in Brazil, Australia and United States. Frequent co-authors include Maria Carolina Monard, Eamonn Keogh, Thanawin Rakthanmanon, Qiang Zhu, Bilson Campana, Brandon Westover, Abdullah Mueen, Jesin Zakaria, Ronaldo C. Prati and Agenor Mafra‐Neto. Their work appears in journals such as Expert Systems with Applications, Neurocomputing and IEEE Transactions on Knowledge and Data Engineering.
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.