Marco Pedicini

59 total papers · 434 total citations
24 papers, 168 citations indexed

About

Marco Pedicini is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Mathematical Physics. According to data from OpenAlex, Marco Pedicini has authored 24 papers receiving a total of 168 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 14 papers in Computational Theory and Mathematics and 4 papers in Mathematical Physics. Recurrent topics in Marco Pedicini's work include Logic, programming, and type systems (6 papers), semigroups and automata theory (6 papers) and Coding theory and cryptography (5 papers). Marco Pedicini is often cited by papers focused on Logic, programming, and type systems (6 papers), semigroups and automata theory (6 papers) and Coding theory and cryptography (5 papers). Marco Pedicini collaborates with scholars based in Italy, France and Sweden. Marco Pedicini's co-authors include Filippo Castiglione, Daniele Santoni, Vilmos Komornik, Paola Loreti, Eivind Hovig, Trevor Clancy, Francesco Quaglia, Mikael Benson, Vegard Nygaard and Fredrik Barrenäs and has published in prestigious journals such as Bioinformatics, PLoS Computational Biology and Theoretical Computer Science.

In The Last Decade

Marco Pedicini

18 papers receiving 157 citations

Author Peers

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

Author Last Decade Papers Cites
Marco Pedicini 67 58 44 34 29 24 168
Luis David García Puente 87 1.3× 38 0.7× 58 1.3× 14 0.4× 9 0.3× 18 221
Yu Gu 21 0.3× 44 0.8× 73 1.7× 24 0.7× 17 0.6× 26 282
Bernhard Reus 118 1.8× 188 3.2× 7 0.2× 11 0.3× 43 1.5× 29 272
Jake P. Taylor‐King 77 1.1× 49 0.8× 138 3.1× 12 0.4× 5 0.2× 14 267
Gleb Pogudin 23 0.3× 13 0.2× 49 1.1× 3 0.1× 8 0.3× 27 158
Mark Sellke 22 0.3× 41 0.7× 9 0.2× 20 0.6× 2 0.1× 27 134
Akitoshi Kawamura 65 1.0× 24 0.4× 16 0.4× 6 0.2× 10 0.3× 35 182
Verónica Becher 116 1.7× 79 1.4× 41 0.9× 19 0.6× 32 169
Matthew Macauley 64 1.0× 17 0.3× 100 2.3× 10 0.3× 2 0.1× 24 213
Xingwu Liu 11 0.2× 33 0.6× 23 0.5× 2 0.1× 16 0.6× 34 123

Countries citing papers authored by Marco Pedicini

Since Specialization
Citations

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

Fields of papers citing papers by Marco Pedicini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Pedicini

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Pedicini. A scholar is included among the top collaborators of Marco Pedicini 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 Marco Pedicini. Marco Pedicini 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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