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 15
- Evolutionary Algorithms and Applications 8
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- Advanced Image and Video Retrieval Techniques 3
- Co-authors
- Erik Cuevas (22 shared papers)Daniel Zaldívar (6 shared papers)Adrián González (14 shared papers)Bernardo Morales-Castañeda (3 shared papers)Marco Pérez‐Cisneros (9 shared papers)Alma Rodríguez (1 shared paper)Arturo Valdivia (6 shared papers)Ángel G. Andrade (1 shared paper)
In The Last Decade
Fernando Fausto
24 papers receiving 991 citations
Fernando Fausto's Hit Papers
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 592
- Computational Theory and Mathematics 291
- Industrial and Manufacturing Engineering 82
- Computer Vision and Pattern Recognition 162
- Energy Engineering and Power Technology 20
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
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A better balance in metaheuristic algorithms: Does it exist? Hit paper breakdown → | 2020 | 314 |
| 2 | 2019 | 148 | |
| 3 | 2017 | 135 | |
| 4 | 2019 | 56 | |
| 5 | 2018 | 54 | |
| 6 | 2019 | 48 | |
| 7 | 2015 | 38 | |
| 8 | 2019 | 37 | |
| 9 | 2020 | 36 | |
| 10 | 2017 | 25 | |
| 11 | 2017 | 19 | |
| 12 | 2017 | 14 | |
| 13 | 2018 | 13 | |
| 14 | 2017 | 12 | |
| 15 | 2019 | 11 | |
| 16 | 2019 | 10 | |
| 17 | 2019 | 9 | |
| 18 | 2019 | 8 | |
| 19 | 2021 | 5 | |
| 20 | 2019 | 5 |
About Fernando Fausto
Fernando Fausto is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Media Technology and Cellular and Molecular Neuroscience, having authored 24 papers that have together received 1.0k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (15 papers), Evolutionary Algorithms and Applications (8 papers), Advanced Multi-Objective Optimization Algorithms (6 papers), Advanced Image and Video Retrieval Techniques (3 papers), Neurobiology and Insect Physiology Research (2 papers), Robotics and Sensor-Based Localization (2 papers), Advanced Image Fusion Techniques (1 paper) and Electric Vehicles and Infrastructure (1 paper). The work is most often cited by research in Artificial Intelligence (592 citations), Computational Theory and Mathematics (291 citations), Industrial and Manufacturing Engineering (82 citations), Computer Vision and Pattern Recognition (162 citations) and Energy Engineering and Power Technology (20 citations). Fernando Fausto has collaborated with scholars based in Mexico, Germany and India. Frequent co-authors include Erik Cuevas, Daniel Zaldívar, Adrián González, Bernardo Morales-Castañeda, Marco Pérez‐Cisneros, Alma Rodríguez, Arturo Valdivia, Ángel G. Andrade, Ram Sarkar and Raúl Rojas. Their work appears in journals such as Energies, Applied Soft Computing, Applied Intelligence, Swarm and Evolutionary Computation and Artificial Intelligence Review.
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.