Júlia Couto
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Daniel BarbaráYi LiSushil JajodiaNingning WuDuncan D. RuizRafael PrikladnickiJia‐Ling LinFelipe Meneguzzi
- Topics
- Data Mining Algorithms and Applications (5 papers)Data Management and Algorithms (5 papers)Software Engineering Research (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaACM SIGMOD RecordInternational Journal of Intelligent Systems
- Partner nations
- BrazilUnited StatesCanada
In The Last Decade
Júlia Couto
24 papers receiving 498 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 421
- Computer Networks and Communications 199
- Signal Processing 184
- Information Systems 163
- Computer Vision and Pattern Recognition 86
Countries citing papers authored by Júlia Couto
This map shows the geographic impact of Júlia Couto'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 Júlia Couto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Júlia Couto more than expected).
Fields of papers citing papers by Júlia Couto
This network shows the impact of papers produced by Júlia Couto. 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 Júlia Couto. The network helps show where Júlia Couto may publish in the future.
Co-authorship network of co-authors of Júlia Couto
This figure shows the co-authorship network connecting the top 25 collaborators of Júlia Couto. A scholar is included among the top collaborators of Júlia Couto 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 Júlia Couto. Júlia Couto 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 | 1 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 6 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 15 | |
| 11 | 1 | |
| 12 | 7 | |
| 13 | 18 | |
| 14 | The TERRAIN tool for teaching responsible research and innovation | 3 |
| 15 | 0 | |
| 16 | 24 | |
| 17 | 2 | |
| 18 | 66 | |
| 19 | 154 | |
| 20 | 2 |
About Júlia Couto
Júlia Couto is a scholar working on Health Informatics, Health Information Management and Signal Processing, having authored 25 papers that have together received 553 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (5 papers), Data Management and Algorithms (5 papers) and Software Engineering Research (4 papers). The work is most often cited by research in Signal Processing (184 citations), Artificial Intelligence (421 citations) and Computer Networks and Communications (199 citations). Júlia Couto has collaborated with scholars based in Brazil, United States and Canada. Frequent co-authors include Daniel Barbará, Yi Li, Sushil Jajodia, Ningning Wu, Yi Li, Duncan D. Ruiz, Rafael Prikladnicki, Jia‐Ling Lin, Felipe Meneguzzi and Sabrina Marczak. Their work appears in journals such as SHILAP Revista de lepidopterología, ACM SIGMOD Record and International Journal of Intelligent 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.