Daniel Rivero

54 papers and 1.6k indexed citations i.

About

Daniel Rivero is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Daniel Rivero has authored 54 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 9 papers in Cognitive Neuroscience and 8 papers in Molecular Biology. Recurrent topics in Daniel Rivero’s work include Evolutionary Algorithms and Applications (14 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Neural Networks and Applications (9 papers). Daniel Rivero is often cited by papers focused on Evolutionary Algorithms and Applications (14 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Neural Networks and Applications (9 papers). Daniel Rivero collaborates with scholars based in Spain, Ecuador and United States. Daniel Rivero's co-authors include Alejandro Pazos, Ling Guo, Julián Dorado, Enrique Fernández-Blanco, Juan R. Rabuñal, Cristian R. Munteanu, Miguel R. Luaces, Jerónimo Puertas, Joaquín Suárez and Alfonso Saiz‐Lopez and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and Physical Chemistry Chemical Physics.

In The Last Decade

Co-authorship network of co-authors of Daniel Rivero i

Fields of papers citing papers by Daniel Rivero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniel Rivero

Since Specialization
Citations

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

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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2025