Rocío Aláiz-Rodríguez
- Artificial Intelligence top 2%
- Information Systems top 5%
- Electrical and Electronic Engineering
- Mechanical Engineering top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Enrique AlegreNitesh V. ChawlaJose G. Moreno-TorresTroy RaederFrancisco HerreraV́ıctor González-CastroEduardo FidalgoFrancisco Jáñez-Martino
- Topics
- Spam and Phishing Detection (10 papers)Imbalanced Data Classification Techniques (7 papers)Machine Learning and Data Classification (6 papers)
In The Last Decade
Rocío Aláiz-Rodríguez
39 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Artificial Intelligence 638
- Information Systems 180
- Electrical and Electronic Engineering 178
- Mechanical Engineering 175
- Computer Vision and Pattern Recognition 170
Countries citing papers authored by Rocío Aláiz-Rodríguez
This map shows the geographic impact of Rocío Aláiz-Rodríguez'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 Rocío Aláiz-Rodríguez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rocío Aláiz-Rodríguez more than expected).
Fields of papers citing papers by Rocío Aláiz-Rodríguez
This network shows the impact of papers produced by Rocío Aláiz-Rodríguez. 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 Rocío Aláiz-Rodríguez. The network helps show where Rocío Aláiz-Rodríguez may publish in the future.
Co-authorship network of co-authors of Rocío Aláiz-Rodríguez
This figure shows the co-authorship network connecting the top 25 collaborators of Rocío Aláiz-Rodríguez. A scholar is included among the top collaborators of Rocío Aláiz-Rodríguez 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 Rocío Aláiz-Rodríguez. Rocío Aláiz-Rodríguez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 12 | |
| 4 | 21 | |
| 5 | 1 | |
| 6 | 27 | |
| 7 | 1 | |
| 8 | Assessment and Estimation of Face Detection Performance Based on Deep Learning for Forensic Applicationsbreakdown → | 241 |
| 9 | 4 | |
| 10 | 13 | |
| 11 | 37 | |
| 12 | 73 | |
| 13 | 23 | |
| 14 | A unifying view on dataset shift in classificationbreakdown → | 531 |
| 15 | 16 | |
| 16 | 16 | |
| 17 | 8 | |
| 18 | Minimax Regret Classifier for Imprecise Class Distributions | 11 |
| 19 | 5 | |
| 20 | 17 |
About Rocío Aláiz-Rodríguez
Rocío Aláiz-Rodríguez is a scholar working on Artificial Intelligence, Signal Processing and Information Systems, having authored 40 papers that have together received 1.4k indexed citations. Recurring topics across this work include Spam and Phishing Detection (10 papers), Imbalanced Data Classification Techniques (7 papers) and Machine Learning and Data Classification (6 papers). The work is most often cited by research in Health Informatics (28 citations), Artificial Intelligence (638 citations) and Industrial and Manufacturing Engineering (117 citations). Rocío Aláiz-Rodríguez has collaborated with scholars based in Spain, Ireland and Australia. Frequent co-authors include Enrique Alegre, Nitesh V. Chawla, Jose G. Moreno-Torres, Troy Raeder, Francisco Herrera, V́ıctor González-Castro, Eduardo Fidalgo, Francisco Jáñez-Martino, María Teresa García-Ordás and Deisy Chaves. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Sensors.
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.