Mario Andrés Muñoz
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 2%
- Industrial and Manufacturing Engineering top 5%
- Control and Systems Engineering top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Kate Smith‐MilesMichael KirleySaman HalgamugeYuan SunSevvandi KandanaarachchiLaura VillanovaDavaatseren BaatarRob J. Hyndman
- Topics
- Metaheuristic Optimization Algorithms Research (24 papers)Advanced Multi-Objective Optimization Algorithms (20 papers)Evolutionary Algorithms and Applications (12 papers)
- Cited by
- Computational Theory and MathematicsArtificial IntelligenceIndustrial and Manufacturing Engineering
- Partner nations
- AustraliaColombiaUnited Kingdom
In The Last Decade
Mario Andrés Muñoz
45 papers receiving 833 citations
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 477
- Computational Theory and Mathematics 265
- Industrial and Manufacturing Engineering 91
- Control and Systems Engineering 87
- Computer Networks and Communications 73
Countries citing papers authored by Mario Andrés Muñoz
This map shows the geographic impact of Mario Andrés Muñoz'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 Mario Andrés Muñoz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Andrés Muñoz more than expected).
Fields of papers citing papers by Mario Andrés Muñoz
This network shows the impact of papers produced by Mario Andrés Muñoz. 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 Mario Andrés Muñoz. The network helps show where Mario Andrés Muñoz may publish in the future.
Co-authorship network of co-authors of Mario Andrés Muñoz
This figure shows the co-authorship network connecting the top 25 collaborators of Mario Andrés Muñoz. A scholar is included among the top collaborators of Mario Andrés Muñoz 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 Mario Andrés Muñoz. Mario Andrés Muñoz 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 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 9 | |
| 10 | 16 | |
| 11 | 5 | |
| 12 | 10 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 12 | |
| 16 | Instance Space Analysis for Unsupervised Outlier Detection | 3 |
| 17 | 18 | |
| 18 | 44 | |
| 19 | 23 | |
| 20 | 5 |
About Mario Andrés Muñoz
Mario Andrés Muñoz is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Statistics and Probability, having authored 55 papers that have together received 857 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (24 papers), Advanced Multi-Objective Optimization Algorithms (20 papers) and Evolutionary Algorithms and Applications (12 papers). The work is most often cited by research in Computational Theory and Mathematics (265 citations), Artificial Intelligence (477 citations) and Industrial and Manufacturing Engineering (91 citations). Mario Andrés Muñoz has collaborated with scholars based in Australia, Colombia and United Kingdom. Frequent co-authors include Kate Smith‐Miles, Michael Kirley, Saman Halgamuge, Yuan Sun, Sevvandi Kandanaarachchi, Laura Villanova, Davaatseren Baatar, Rob J. Hyndman, Eduardo Caicedo and Peter Pivonka. Their work appears in journals such as European Journal of Operational Research, Journal of Biomechanics and ACM Computing Surveys.
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.