Matteo Polettini

64 total papers · 1.1k total citations
27 papers, 641 citations indexed

About

Matteo Polettini is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Matteo Polettini has authored 27 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Statistical and Nonlinear Physics, 9 papers in Cognitive Neuroscience and 5 papers in Molecular Biology. Recurrent topics in Matteo Polettini's work include Advanced Thermodynamics and Statistical Mechanics (25 papers), Statistical Mechanics and Entropy (9 papers) and Neural dynamics and brain function (8 papers). Matteo Polettini is often cited by papers focused on Advanced Thermodynamics and Statistical Mechanics (25 papers), Statistical Mechanics and Entropy (9 papers) and Neural dynamics and brain function (8 papers). Matteo Polettini collaborates with scholars based in Luxembourg, France and Brazil. Matteo Polettini's co-authors include Massimiliano Esposito, Gatien Verley, Alexandre Lazarescu, Jordan M. Horowitz, Gili Bisker, Todd R. Gingrich, Bernhard Altaner, Vivien Lecomte, Izaak Neri and Édgar Roldán and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and Europhysics Letters (EPL).

In The Last Decade

Matteo Polettini

26 papers receiving 635 citations

Author Peers

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

Author						Papers	Cites
Matteo Polettini	571	150	143	100	93	27	641
David Andrieux	653 1.1×	353 2.4×	81 0.6×	121 1.2×	85 0.9×	19	769
Sosuke Ito	514 0.9×	160 1.1×	172 1.2×	104 1.0×	77 0.8×	31	615
Chulan Kwon	452 0.8×	138 0.9×	66 0.5×	63 0.6×	37 0.4×	39	629
Ignacio A. Martínez	567 1.0×	309 2.1×	75 0.5×	49 0.5×	61 0.7×	19	705
Gianmaria Falasco	485 0.8×	158 1.1×	72 0.5×	74 0.7×	48 0.5×	31	600
Raphaël Chétrite	638 1.1×	304 2.0×	101 0.7×	74 0.7×	43 0.5×	22	767
Luis Dinís	452 0.8×	190 1.3×	42 0.3×	175 1.8×	31 0.3×	26	744
Dibyendu Mandal	531 0.9×	255 1.7×	138 1.0×	36 0.4×	29 0.3×	14	577
Izaak Neri	446 0.8×	138 0.9×	70 0.5×	107 1.1×	17 0.2×	32	666
Viktor Holubec	556 1.0×	154 1.0×	33 0.2×	23 0.2×	60 0.6×	38	669

Countries citing papers authored by Matteo Polettini

Since Specialization

Citations

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

Fields of papers citing papers by Matteo Polettini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Polettini

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