Carlos A. Brizuela
- Molecular Biology
- Electrical and Electronic Engineering top 10%
- Aerospace Engineering top 5%
- Computational Theory and Mathematics top 2%
- Artificial Intelligence top 5%
- Co-authors
- Marco A. PanduroBenjamı́n BaránChristian von LückenLuz I. BalderasD. AcostaCésar R. García‐JacasDavid H. CovarrubiasMichael K. Gilson
- Topics
- Antimicrobial Peptides and Activities (13 papers)Scheduling and Optimization Algorithms (13 papers)Metaheuristic Optimization Algorithms Research (11 papers)
- Partner nations
- MexicoParaguayUnited States
In The Last Decade
Carlos A. Brizuela
79 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Molecular Biology 419
- Electrical and Electronic Engineering 366
- Aerospace Engineering 360
- Computational Theory and Mathematics 316
- Artificial Intelligence 234
Countries citing papers authored by Carlos A. Brizuela
This map shows the geographic impact of Carlos A. Brizuela'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 Carlos A. Brizuela with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos A. Brizuela more than expected).
Fields of papers citing papers by Carlos A. Brizuela
This network shows the impact of papers produced by Carlos A. Brizuela. 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 Carlos A. Brizuela. The network helps show where Carlos A. Brizuela may publish in the future.
Co-authorship network of co-authors of Carlos A. Brizuela
This figure shows the co-authorship network connecting the top 25 collaborators of Carlos A. Brizuela. A scholar is included among the top collaborators of Carlos A. Brizuela 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 Carlos A. Brizuela. Carlos A. Brizuela 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 | 20 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 14 | |
| 6 | 36 | |
| 7 | 41 | |
| 8 | 12 | |
| 9 | 31 | |
| 10 | 28 | |
| 11 | 66 | |
| 12 | 5 | |
| 13 | 18 | |
| 14 | Evolutionary Learning of Dynamic Naive Bayesian Classifiers. | 4 |
| 15 | 14 | |
| 16 | 4 | |
| 17 | 9 | |
| 18 | A selection scheme in Genetic Algorithms for a complex scheduling problem | 1 |
| 19 | 0 | |
| 20 | A Diversity Study of Genetic Algorithms for Job Shop Scheduling Problems | 2 |
About Carlos A. Brizuela
Carlos A. Brizuela is a scholar working on Microbiology, Industrial and Manufacturing Engineering and Computational Theory and Mathematics, having authored 85 papers that have together received 1.4k indexed citations. Recurring topics across this work include Antimicrobial Peptides and Activities (13 papers), Scheduling and Optimization Algorithms (13 papers) and Metaheuristic Optimization Algorithms Research (11 papers). The work is most often cited by research in Microbiology (204 citations), Computational Theory and Mathematics (316 citations) and Aerospace Engineering (360 citations). Carlos A. Brizuela has collaborated with scholars based in Mexico, Paraguay and United States. Frequent co-authors include Marco A. Panduro, Benjamı́n Barán, Christian von Lücken, Luz I. Balderas, D. Acosta, César R. García‐Jacas, David H. Covarrubias, Michael K. Gilson, Yovani Marrero‐Ponce and Sergio A. Águila. Their work appears in journals such as Bioinformatics, PLoS ONE and Scientific Reports.
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.