Franco Turini

142 total papers · 4.6k total citations
65 papers, 1.5k citations indexed

About

Franco Turini is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Franco Turini has authored 65 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Artificial Intelligence, 21 papers in Information Systems and 21 papers in Signal Processing. Recurrent topics in Franco Turini's work include Data Management and Algorithms (17 papers), Data Mining Algorithms and Applications (15 papers) and Logic, programming, and type systems (12 papers). Franco Turini is often cited by papers focused on Data Management and Algorithms (17 papers), Data Mining Algorithms and Applications (15 papers) and Logic, programming, and type systems (12 papers). Franco Turini collaborates with scholars based in Italy, Switzerland and Kazakhstan. Franco Turini's co-authors include Salvatore Ruggieri, Dino Pedreschi, Fosca Giannotti, Riccardo Guidotti, Anna Monreale, Antonio Brogi, Andrea Romei, Paolo Mancarella, Michele Berlingerio and Francesco Bonchi and has published in prestigious journals such as Communications of the ACM, Expert Systems with Applications and IEEE Transactions on Software Engineering.

In The Last Decade

Franco Turini

60 papers receiving 1.5k citations

Author Peers

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

Author Last Decade Papers Cites
Franco Turini 1.1k 505 274 194 135 65 1.5k
Himabindu Lakkaraju 1.3k 1.2× 310 0.6× 199 0.7× 213 1.1× 108 0.8× 44 2.1k
Julia Stoyanovich 734 0.7× 362 0.7× 380 1.4× 142 0.7× 265 2.0× 92 1.4k
Adrian Weller 835 0.7× 480 1.0× 114 0.4× 171 0.9× 53 0.4× 85 1.6k
Krishnaram Kenthapadi 1.2k 1.1× 95 0.2× 387 1.4× 346 1.8× 163 1.2× 66 1.7k
Sameep Mehta 477 0.4× 262 0.5× 310 1.1× 173 0.9× 66 0.5× 80 1.3k
Anna Monreale 917 0.8× 101 0.2× 263 1.0× 192 1.0× 110 0.8× 82 1.9k
Julia Rubin 1.1k 1.0× 371 0.7× 1.2k 4.5× 108 0.6× 57 0.4× 67 2.0k
Chenhao Tan 838 0.7× 116 0.2× 241 0.9× 234 1.2× 113 0.8× 88 1.5k
Roman V. Yampolskiy 458 0.4× 204 0.4× 508 1.9× 129 0.7× 57 0.4× 124 1.5k
Judy Goldsmith 666 0.6× 181 0.4× 92 0.3× 55 0.3× 144 1.1× 105 1.3k

Countries citing papers authored by Franco Turini

Since Specialization
Citations

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

Fields of papers citing papers by Franco Turini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Franco Turini

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