Matteo Fraschini

133 total papers · 1.7k total citations
64 papers, 1.2k citations indexed

About

Matteo Fraschini is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Matteo Fraschini has authored 64 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cognitive Neuroscience, 8 papers in Computer Vision and Pattern Recognition and 7 papers in Molecular Biology. Recurrent topics in Matteo Fraschini's work include EEG and Brain-Computer Interfaces (21 papers), Functional Brain Connectivity Studies (20 papers) and Neural dynamics and brain function (15 papers). Matteo Fraschini is often cited by papers focused on EEG and Brain-Computer Interfaces (21 papers), Functional Brain Connectivity Studies (20 papers) and Neural dynamics and brain function (15 papers). Matteo Fraschini collaborates with scholars based in Italy, Netherlands and United States. Matteo Fraschini's co-authors include Matteo Demuru, Arjan Hillebrand, Francesco Marrosu, Luca Didaci, Gian Luca Marcialis, Cornelis J. Stam, Michael A. Wirth, Jennifer A. Lyon, Monica Puligheddu and Luca Saba and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neurology and Scientific Reports.

In The Last Decade

Matteo Fraschini

55 papers receiving 1.1k citations

Author Peers

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

Author Last Decade Papers Cites
Matteo Fraschini 798 168 121 96 94 64 1.2k
Simona De Salvo 680 0.9× 103 0.6× 201 1.7× 145 1.5× 73 0.8× 68 1.2k
Ramachandran Ramani 715 0.9× 165 1.0× 91 0.8× 57 0.6× 270 2.9× 28 1.2k
Jiaxiang Zhang 949 1.2× 131 0.8× 46 0.4× 85 0.9× 64 0.7× 64 1.5k
Francisco J. Fraga 973 1.2× 156 0.9× 140 1.2× 40 0.4× 49 0.5× 61 1.3k
Catherine M. Sweeney‐Reed 718 0.9× 252 1.5× 110 0.9× 146 1.5× 51 0.5× 57 1.2k
Xue Wang 563 0.7× 108 0.6× 113 0.9× 105 1.1× 196 2.1× 43 1.0k
Long Chen 680 0.9× 337 2.0× 82 0.7× 47 0.5× 92 1.0× 66 1.1k
Francisco Gómez 876 1.1× 105 0.6× 48 0.4× 206 2.1× 246 2.6× 57 1.3k
Willy Wong 698 0.9× 136 0.8× 334 2.8× 117 1.2× 56 0.6× 84 1.3k
Karin van der Hiele 488 0.6× 125 0.7× 109 0.9× 152 1.6× 176 1.9× 38 1.1k

Countries citing papers authored by Matteo Fraschini

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Fraschini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Fraschini

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Fraschini. A scholar is included among the top collaborators of Matteo Fraschini 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 Matteo Fraschini. Matteo Fraschini 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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2026