Francesco Gullo

108 total papers · 2.0k total citations
64 papers, 1.1k citations indexed

About

Francesco Gullo is a scholar working on Artificial Intelligence, Signal Processing and Statistical and Nonlinear Physics. According to data from OpenAlex, Francesco Gullo has authored 64 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 24 papers in Signal Processing and 21 papers in Statistical and Nonlinear Physics. Recurrent topics in Francesco Gullo's work include Data Management and Algorithms (22 papers), Complex Network Analysis Techniques (21 papers) and Advanced Clustering Algorithms Research (19 papers). Francesco Gullo is often cited by papers focused on Data Management and Algorithms (22 papers), Complex Network Analysis Techniques (21 papers) and Advanced Clustering Algorithms Research (19 papers). Francesco Gullo collaborates with scholars based in Italy, Spain and United States. Francesco Gullo's co-authors include Francesco Bonchi, Andrea Tagarelli, Aristides Gionis, Giovanni Ponti, Charalampos E. Tsourakakis, Maria A. Tsiarli, Sergio Greco, Andreas Kaltenbrunner, Yana Volkovich and Nicola Barbieri and has published in prestigious journals such as Pattern Recognition, Information Sciences and Physics Letters A.

In The Last Decade

Francesco Gullo

60 papers receiving 1.1k citations

Author Peers

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

Author						Papers	Cites
Francesco Gullo	587	486	300	287	264	64	1.1k
Flavio Chierichetti	448 0.8×	418 0.9×	161 0.5×	306 1.1×	395 1.5×	55	1.1k
Neil Shah	920 1.6×	283 0.6×	303 1.0×	222 0.8×	305 1.2×	67	1.4k
Siqiang Luo	431 0.7×	464 1.0×	356 1.2×	263 0.9×	536 2.0×	64	1.1k
Silvio Lattanzi	696 1.2×	646 1.3×	185 0.6×	344 1.2×	530 2.0×	64	1.5k
James Abello	325 0.6×	304 0.6×	254 0.8×	657 2.3×	170 0.6×	51	1.2k
Reid Andersen	552 0.9×	602 1.2×	136 0.5×	224 0.8×	370 1.4×	25	1.2k
Sayan Ranu	264 0.4×	223 0.5×	305 1.0×	202 0.7×	192 0.7×	63	928
Mauro Sozio	494 0.8×	289 0.6×	184 0.6×	157 0.5×	366 1.4×	33	919
Sibo Wang	456 0.8×	368 0.8×	365 1.2×	306 1.1×	386 1.5×	95	1.2k
Xiaoyang Wang	396 0.7×	435 0.9×	134 0.4×	139 0.5×	191 0.7×	94	949

Countries citing papers authored by Francesco Gullo

Since Specialization

Citations

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

Fields of papers citing papers by Francesco Gullo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Gullo

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