Carlos A. Brizuela
- Microbiology top 2%
- Antimicrobial Peptides and Activities 13
-
- Advanced Multi-Objective Optimization Algorithms 10
- Computational Drug Discovery Methods 10
- Aerospace Engineering top 5%
- Antenna Design and Optimization 11
- Antenna Design and Analysis 10
-
- Scheduling and Optimization Algorithms 13
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research 11
-
- Microwave Engineering and Waveguides 10
- Co-authors
- Marco A. PanduroBenjamı́n BaránChristian von LückenLuz I. BalderasD. AcostaCésar R. García‐JacasDavid H. CovarrubiasMichael K. Gilson
- 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
- Microbiology 204
- Computational Theory and Mathematics 316
- Aerospace Engineering 360
- Industrial and Manufacturing Engineering 102
- 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
The 25 scholars most cited alongside Carlos A. Brizuela, 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 | 2025 | 2 | |
| 2 | 2025 | 20 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 14 | |
| 6 | 2022 | 36 | |
| 7 | 2020 | 41 | |
| 8 | 2020 | 12 | |
| 9 | 2019 | 31 | |
| 10 | 2018 | 28 | |
| 11 | 2015 | 66 | |
| 12 | 2009 | 5 | |
| 13 | 2009 | 18 | |
| 14 | Evolutionary Learning of Dynamic Naive Bayesian Classifiers. | 2008 | 4 |
| 15 | 2008 | 14 | |
| 16 | 2007 | 4 | |
| 17 | 2006 | 9 | |
| 18 | A selection scheme in Genetic Algorithms for a complex scheduling problem | 2000 | 1 |
| 19 | 2000 | 0 | |
| 20 | A Diversity Study of Genetic Algorithms for Job Shop Scheduling Problems | 1999 | 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), Metaheuristic Optimization Algorithms Research (11 papers), Antenna Design and Optimization (11 papers), Microwave Engineering and Waveguides (10 papers), Advanced Multi-Objective Optimization Algorithms (10 papers), Computational Drug Discovery Methods (10 papers) and Antenna Design and Analysis (10 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.