Matteo Farinella

1.1k total citations
10 papers, 713 citations indexed

About

Matteo Farinella is a scholar working on Speech and Hearing, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Matteo Farinella has authored 10 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Speech and Hearing, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Cognitive Neuroscience. Recurrent topics in Matteo Farinella's work include Digital Storytelling and Education (5 papers), Neural dynamics and brain function (3 papers) and Comics and Graphic Narratives (3 papers). Matteo Farinella is often cited by papers focused on Digital Storytelling and Education (5 papers), Neural dynamics and brain function (3 papers) and Comics and Graphic Narratives (3 papers). Matteo Farinella collaborates with scholars based in United States, United Kingdom and France. Matteo Farinella's co-authors include R. Angus Silver, Padraig Gleeson, Dave Murray-Rust, Benjamin Bach, Zezhong Wang, Nathalie Henry Riche, Zoltán Nusser, Koen Vervaeke, Andrea Lőrincz and Michael L. Hines and has published in prestigious journals such as Neuron, SHILAP Revista de lepidopterología and PLoS Computational Biology.

In The Last Decade

Matteo Farinella

9 papers receiving 689 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matteo Farinella United States 8 229 184 151 117 87 10 713
Branka Špehar Australia 26 2.1k 9.3× 136 0.7× 121 0.8× 364 3.1× 20 0.2× 88 2.7k
E. Bruce Goldstein United States 18 470 2.1× 215 1.2× 283 1.9× 119 1.0× 53 0.6× 31 1.3k
Ming Meng United States 16 1.3k 5.7× 106 0.6× 74 0.5× 123 1.1× 23 0.3× 63 1.8k
Ignacio Vallines Germany 7 908 4.0× 45 0.2× 24 0.2× 89 0.8× 30 0.3× 10 1.1k
Bart Farell United States 16 1.3k 5.8× 142 0.8× 89 0.6× 206 1.8× 12 0.1× 61 1.6k
Samuel A. Nastase United States 18 1.0k 4.5× 41 0.2× 23 0.2× 78 0.7× 31 0.4× 51 1.3k
Dejan Todorović Serbia 16 821 3.6× 46 0.3× 24 0.2× 244 2.1× 17 0.2× 48 1.1k
R. Beau Lotto United Kingdom 20 636 2.8× 233 1.3× 187 1.2× 109 0.9× 25 0.3× 44 1.2k
Jan Drugowitsch United States 21 1.4k 6.0× 234 1.3× 147 1.0× 33 0.3× 41 0.5× 55 1.9k
Gidon Felsen United States 18 990 4.3× 535 2.9× 116 0.8× 64 0.5× 32 0.4× 39 1.3k

Countries citing papers authored by Matteo Farinella

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Farinella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Farinella

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

All Works

10 of 10 papers shown
1.
Muscio, Alessandro & Matteo Farinella. (2025). Are scientists heroes or villains? The fascinating case of DC and Marvel superheroes comics. Technology in Society. 82. 102895–102895.
2.
Wang, Zezhong, et al.. (2019). Comparing Effectiveness and Engagement of Data Comics and Infographics. Edinburgh Research Explorer. 1–12. 61 indexed citations
3.
Farinella, Matteo & Lingani Mbakile‐Mahlanza. (2019). Making the Brain Accessible with Comics. World Neurosurgery. 133. 426–430. 2 indexed citations
4.
Farinella, Matteo. (2018). The potential of comics in science communication. Journal of Science Communication. 17(1). Y01–Y01. 140 indexed citations
5.
Farinella, Matteo. (2018). Of Microscopes and Metaphors: Visual Analogy as a Scientific Tool. SHILAP Revista de lepidopterología. 8(1). 7 indexed citations
6.
Farinella, Matteo. (2018). Science Comics' Super Powers. American Scientist. 106(4). 218–218. 7 indexed citations
7.
Bach, Benjamin, Zezhong Wang, Matteo Farinella, Dave Murray-Rust, & Nathalie Henry Riche. (2018). Design Patterns for Data Comics. Edinburgh Research Explorer (University of Edinburgh). 1–12. 100 indexed citations
8.
Farinella, Matteo, et al.. (2014). Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model. PLoS Computational Biology. 10(4). e1003590–e1003590. 25 indexed citations
9.
Vervaeke, Koen, Andrea Lőrincz, Padraig Gleeson, et al.. (2010). Rapid Desynchronization of an Electrically Coupled Interneuron Network with Sparse Excitatory Synaptic Input. Neuron. 67(3). 435–451. 165 indexed citations
10.
Gleeson, Padraig, Sharon Crook, Robert C. Cannon, et al.. (2010). NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail. PLoS Computational Biology. 6(6). e1000815–e1000815. 206 indexed citations

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