Fernando Fausto
Impact in
- Artificial Intelligence top 2%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Machine Learning and ELM
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Metaheuristic Optimization Algorithms Research 9
- Evolutionary Algorithms and Applications 7
- Solar Radiation and Photovoltaics 1
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- Advanced Image and Video Retrieval Techniques 3
- Digital Imaging for Blood Diseases 1
- Co-authors
- Erik Cuevas (15 shared papers)Daniel Zaldívar (6 shared papers)Bernardo Morales-Castañeda (3 shared papers)Adrián González (7 shared papers)Alma Rodríguez (1 shared paper)Marco Pérez‐Cisneros (9 shared papers)Arturo Valdivia (6 shared papers)Ángel G. Andrade (1 shared paper)
In The Last Decade
Fernando Fausto
17 papers receiving 800 citations
Fernando Fausto's Hit Papers
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 490
- Computational Theory and Mathematics 242
- Computer Vision and Pattern Recognition 133
- Industrial and Manufacturing Engineering 64
- Energy Engineering and Power Technology 18
Countries citing papers authored by Fernando Fausto
This map shows the geographic impact of Fernando Fausto'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 Fernando Fausto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Fausto more than expected).
Fields of papers citing papers by Fernando Fausto
This network shows the impact of papers produced by Fernando Fausto. 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 Fernando Fausto. The network helps show where Fernando Fausto may publish in the future.
Co-authors
The 10 scholars most cited alongside Fernando Fausto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A better balance in metaheuristic algorithms: Does it exist? Hit paper breakdown → | 2020 | 283 |
| 2 | 2019 | 138 | |
| 3 | 2017 | 111 | |
| 4 | 2019 | 56 | |
| 5 | 2018 | 48 | |
| 6 | 2019 | 43 | |
| 7 | 2020 | 34 | |
| 8 | 2017 | 25 | |
| 9 | 2015 | 25 | |
| 10 | 2017 | 19 | |
| 11 | 2017 | 11 | |
| 12 | 2018 | 11 | |
| 13 | 2017 | 9 | |
| 14 | 2021 | 5 | |
| 15 | 2016 | 4 | |
| 16 | 2019 | 2 | |
| 17 | 2024 | 1 |
About Fernando Fausto
Fernando Fausto is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Media Technology and Aerospace Engineering, having authored 17 papers that have together received 825 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (9 papers), Evolutionary Algorithms and Applications (7 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Multi-Objective Optimization Algorithms (3 papers), Robotics and Sensor-Based Localization (2 papers), Solar Radiation and Photovoltaics (1 paper), Digital Imaging for Blood Diseases (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Artificial Intelligence (490 citations), Computational Theory and Mathematics (242 citations), Computer Vision and Pattern Recognition (133 citations), Industrial and Manufacturing Engineering (64 citations) and Energy Engineering and Power Technology (18 citations). Fernando Fausto has collaborated with scholars based in Mexico, India and Germany. Frequent co-authors include Erik Cuevas, Daniel Zaldívar, Bernardo Morales-Castañeda, Adrián González, Alma Rodríguez, Marco Pérez‐Cisneros, Arturo Valdivia, Ángel G. Andrade, Ram Sarkar and Raúl Rojas. Their work appears in journals such as Energies, Applied Intelligence, Biosystems, International Journal of Computational Intelligence Systems and Pattern Analysis and Applications.
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.