Marco Pérez‐Cisneros
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Computational Theory and Mathematics top 1%
- Electrical and Electronic Engineering top 10%
- Control and Systems Engineering top 5%
- Co-authors
- Erik CuevasDaniel ZaldívarDiego OlivaMiguel CienfuegosFernando FaustoHumberto SossaGonzalo PájaresValentín Osuna-Enciso
- Topics
- Metaheuristic Optimization Algorithms Research (42 papers)Evolutionary Algorithms and Applications (24 papers)Advanced Multi-Objective Optimization Algorithms (23 papers)
In The Last Decade
Marco Pérez‐Cisneros
129 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Artificial Intelligence 1.4k
- Computer Vision and Pattern Recognition 956
- Computational Theory and Mathematics 511
- Electrical and Electronic Engineering 481
- Control and Systems Engineering 366
Countries citing papers authored by Marco Pérez‐Cisneros
This map shows the geographic impact of Marco Pérez‐Cisneros'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 Marco Pérez‐Cisneros with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Pérez‐Cisneros more than expected).
Fields of papers citing papers by Marco Pérez‐Cisneros
This network shows the impact of papers produced by Marco Pérez‐Cisneros. 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 Marco Pérez‐Cisneros. The network helps show where Marco Pérez‐Cisneros may publish in the future.
Co-authorship network of co-authors of Marco Pérez‐Cisneros
This figure shows the co-authorship network connecting the top 25 collaborators of Marco Pérez‐Cisneros. A scholar is included among the top collaborators of Marco Pérez‐Cisneros 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 Marco Pérez‐Cisneros. Marco Pérez‐Cisneros is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 12 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 39 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | 10 | |
| 14 | 9 | |
| 15 | 5 | |
| 16 | 5 | |
| 17 | 22 | |
| 18 | 55 | |
| 19 | A swarm optimization algorithm inspired in the behavior of the social-spiderbreakdown → | 408 |
| 20 | 21 |
About Marco Pérez‐Cisneros
Marco Pérez‐Cisneros is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics, having authored 144 papers that have together received 3.0k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (42 papers), Evolutionary Algorithms and Applications (24 papers) and Advanced Multi-Objective Optimization Algorithms (23 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (956 citations), Artificial Intelligence (1.4k citations) and Media Technology (293 citations). Marco Pérez‐Cisneros has collaborated with scholars based in Mexico, Spain and India. Frequent co-authors include Erik Cuevas, Daniel Zaldívar, Diego Oliva, Miguel Cienfuegos, Fernando Fausto, Humberto Sossa, Gonzalo Pájares, Valentín Osuna-Enciso, Erick Rodríguez-Esparza and Salvador Hinojosa. Their work appears in journals such as PLoS ONE, Scientific Reports and Expert Systems with 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.