Diego García‐Gil
- Artificial Intelligence top 5%
- Information Systems top 10%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Francisco HerreraSalvador GarcíaJulián LuengoSergio Ramírez‐GallegoIsaac TrigueroJesús MailloM. Martínez-BallesterosJosé C. Riquelme
- Topics
- Imbalanced Data Classification Techniques (6 papers)Anomaly Detection Techniques and Applications (6 papers)Network Security and Intrusion Detection (5 papers)
- Partner nations
- SpainSaudi ArabiaCuba
In The Last Decade
Diego García‐Gil
17 papers receiving 414 citations
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 225
- Information Systems 98
- Computer Networks and Communications 65
- Signal Processing 45
- Computer Vision and Pattern Recognition 43
Countries citing papers authored by Diego García‐Gil
This map shows the geographic impact of Diego García‐Gil'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 Diego García‐Gil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego García‐Gil more than expected).
Fields of papers citing papers by Diego García‐Gil
This network shows the impact of papers produced by Diego García‐Gil. 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 Diego García‐Gil. The network helps show where Diego García‐Gil may publish in the future.
Co-authorship network of co-authors of Diego García‐Gil
This figure shows the co-authorship network connecting the top 25 collaborators of Diego García‐Gil. A scholar is included among the top collaborators of Diego García‐Gil 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 Diego García‐Gil. Diego García‐Gil is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 11 | |
| 7 | 16 | |
| 8 | 31 | |
| 9 | Smart Data based Ensemble for Imbalanced Big Data Classification | 1 |
| 10 | 17 | |
| 11 | 64 | |
| 12 | 1 | |
| 13 | 16 | |
| 14 | 4 | |
| 15 | 139 | |
| 16 | 30 | |
| 17 | 29 | |
| 18 | 61 |
About Diego García‐Gil
Diego García‐Gil is a scholar working on Health Information Management, Artificial Intelligence and Information Systems and Management, having authored 18 papers that have together received 427 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (6 papers), Anomaly Detection Techniques and Applications (6 papers) and Network Security and Intrusion Detection (5 papers). The work is most often cited by research in Artificial Intelligence (225 citations), Health Information Management (23 citations) and Information Systems (98 citations). Diego García‐Gil has collaborated with scholars based in Spain, Saudi Arabia and Cuba. Frequent co-authors include Francisco Herrera, Salvador García, Julián Luengo, Sergio Ramírez‐Gallego, Isaac Triguero, Jesús Maillo, M. Martínez-Ballesteros, José C. Riquelme, Jesús Alcalá‐Fdez and Joshua Zhexue Huang. Their work appears in journals such as Pattern Recognition, Information Sciences and Neurocomputing.
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.