Francesco Masulli

78 papers and 1.2k indexed citations i.

About

Francesco Masulli is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Francesco Masulli has authored 78 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 18 papers in Signal Processing and 16 papers in Computer Vision and Pattern Recognition. Recurrent topics in Francesco Masulli’s work include Neural Networks and Applications (22 papers), Gene expression and cancer classification (10 papers) and Advanced Clustering Algorithms Research (9 papers). Francesco Masulli is often cited by papers focused on Neural Networks and Applications (22 papers), Gene expression and cancer classification (10 papers) and Advanced Clustering Algorithms Research (9 papers). Francesco Masulli collaborates with scholars based in Italy, United States and Switzerland. Francesco Masulli's co-authors include Stefano Rovetta, Maurizio Filippone, Francesco Camastra, Andrea Schenone, Giorgio Valentini, Alessandro E. P. Villa, Włodzisław Duch, Günther Palm, Péter Érdi and Sushmita Mitra and has published in prestigious journals such as Analytica Chimica Acta, Sensors and Actuators B Chemical and Vision Research.

In The Last Decade

Co-authorship network of co-authors of Francesco Masulli i

Fields of papers citing papers by Francesco Masulli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Francesco Masulli

Since Specialization
Citations

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

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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