Mariana Macedo

508 total citations
23 papers, 344 citations indexed

About

Mariana Macedo is a scholar working on Artificial Intelligence, Biomedical Engineering and Sociology and Political Science. According to data from OpenAlex, Mariana Macedo has authored 23 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 4 papers in Biomedical Engineering and 3 papers in Sociology and Political Science. Recurrent topics in Mariana Macedo's work include Metaheuristic Optimization Algorithms Research (12 papers), Evolutionary Algorithms and Applications (8 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Mariana Macedo is often cited by papers focused on Metaheuristic Optimization Algorithms Research (12 papers), Evolutionary Algorithms and Applications (8 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Mariana Macedo collaborates with scholars based in Brazil, United Kingdom and United States. Mariana Macedo's co-authors include Carmelo J. A. Bastos-Filho, Hugo Valadares Siqueira, Anu Gokhale, Elliackin Figueiredo, Ronaldo Menezes, Laura Lotero, Alessio Cardillo, Hugo Barbosa, Diego Pinheiro and P. Santos and has published in prestigious journals such as PLoS ONE, IEEE Access and Biotechnology and Bioengineering.

In The Last Decade

Mariana Macedo

21 papers receiving 336 citations

Peers

Mariana Macedo
Comparison fields: 5 of 93
  • Artificial Intelligence 170
  • Electrical and Electronic Engineering 48
  • Computational Theory and Mathematics 42
  • Biomedical Engineering 34
  • Control and Systems Engineering 29
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Matthias Steinbrecher Germany View profile →
Citations per field, relative to Mariana Macedo
Mariana Macedo · 1×
Citations per year, relative to Mariana Macedo
Mariana Macedo · 1×

Countries citing papers authored by Mariana Macedo

Since Specialization
Citations

This map shows the geographic impact of Mariana Macedo'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 Mariana Macedo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mariana Macedo more than expected).

Fields of papers citing papers by Mariana Macedo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mariana Macedo. 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 Mariana Macedo. The network helps show where Mariana Macedo may publish in the future.

Co-authorship network of co-authors of Mariana Macedo

This figure shows the co-authorship network connecting the top 25 collaborators of Mariana Macedo. A scholar is included among the top collaborators of Mariana Macedo 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 Mariana Macedo. Mariana Macedo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 4
2 3
3 0
4 23
5 3
6 14
7 1
8 19
9 31
10 11
11 27
12 36
13 8
14 53
15 53
16 4
17
Improved Multi-Objective Binary Fish School for Feature Selection.
2
18 12
19 5
20 26

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.

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