Ricardo Cerri

123 total papers · 1.6k total citations
68 papers, 838 citations indexed

About

Ricardo Cerri is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ricardo Cerri has authored 68 papers receiving a total of 838 indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Artificial Intelligence, 30 papers in Molecular Biology and 15 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ricardo Cerri's work include Text and Document Classification Technologies (33 papers), Machine Learning in Bioinformatics (20 papers) and Machine Learning and Data Classification (17 papers). Ricardo Cerri is often cited by papers focused on Text and Document Classification Technologies (33 papers), Machine Learning in Bioinformatics (20 papers) and Machine Learning and Data Classification (17 papers). Ricardo Cerri collaborates with scholars based in Brazil, United Kingdom and Belgium. Ricardo Cerri's co-authors include Rodrigo C. Barros, André C. P. L. F. de Carvalho, Jônatas Wehrmann, Rafael Gomes Mantovani, Sylvio Barbon, Yaochu Jin, Joaquin Vanschoren, Tomáš Horváth, Alex A. Freitas and Saulo Martiello Mastelini and has published in prestigious journals such as Bioinformatics, Expert Systems with Applications and Gene.

In The Last Decade

Ricardo Cerri

61 papers receiving 818 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Ricardo Cerri	492	224	147	117	87	68	838
Vaibhav Rajan	270 0.5×	205 0.9×	72 0.5×	107 0.9×	34 0.4×	61	737
Amr Badr	365 0.7×	131 0.6×	133 0.9×	54 0.5×	73 0.8×	70	1.0k
Pramod Kumar Singh	570 1.2×	63 0.3×	181 1.2×	212 1.8×	138 1.6×	62	938
Juan José del Coz	514 1.0×	102 0.5×	162 1.1×	128 1.1×	28 0.3×	42	941
Marcel Brun	223 0.5×	430 1.9×	100 0.7×	51 0.4×	74 0.9×	59	881
Alneu de Andrade Lopes	415 0.8×	95 0.4×	199 1.4×	116 1.0×	39 0.4×	71	800
Carlos Andrés Peña-Reyes	543 1.1×	182 0.8×	99 0.7×	49 0.4×	64 0.7×	35	855
Harith Al-Sahaf	588 1.2×	65 0.3×	193 1.3×	85 0.7×	95 1.1×	55	943
James McDermott	719 1.5×	188 0.8×	73 0.5×	42 0.4×	132 1.5×	51	985
Shyr-Shen Yu	323 0.7×	97 0.4×	278 1.9×	32 0.3×	135 1.6×	79	709

Countries citing papers authored by Ricardo Cerri

Since Specialization

Citations

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

Fields of papers citing papers by Ricardo Cerri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ricardo Cerri

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

All Works

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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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