Fernando Gama

52 papers and 991 indexed citations i.

About

Fernando Gama is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Electrical and Electronic Engineering. According to data from OpenAlex, Fernando Gama has authored 52 papers receiving a total of 991 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Artificial Intelligence, 20 papers in Statistical and Nonlinear Physics and 12 papers in Electrical and Electronic Engineering. Recurrent topics in Fernando Gama’s work include Advanced Graph Neural Networks (35 papers), Complex Network Analysis Techniques (20 papers) and Topic Modeling (10 papers). Fernando Gama is often cited by papers focused on Advanced Graph Neural Networks (35 papers), Complex Network Analysis Techniques (20 papers) and Topic Modeling (10 papers). Fernando Gama collaborates with scholars based in United States, The Netherlands and Spain. Fernando Gama's co-authors include Alejandro Ribeiro, Luana Ruiz, Antonio G. Marqués, Geert Leus, Joan Bruna, Elvin Isufi, Amanda Prorok, Qingbiao Li, Ekaterina Tolstaya and Santiago Segarra and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the IEEE and IEEE Transactions on Signal Processing.

In The Last Decade

Co-authorship network of co-authors of Fernando Gama i

Fields of papers citing papers by Fernando Gama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Fernando Gama

Since Specialization
Citations

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