Emanuele Principi

122 total papers · 1.9k total citations
75 papers, 1.2k citations indexed

About

Emanuele Principi is a scholar working on Signal Processing, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Emanuele Principi has authored 75 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Signal Processing, 29 papers in Artificial Intelligence and 21 papers in Electrical and Electronic Engineering. Recurrent topics in Emanuele Principi's work include Speech and Audio Processing (26 papers), Music and Audio Processing (19 papers) and Speech Recognition and Synthesis (14 papers). Emanuele Principi is often cited by papers focused on Speech and Audio Processing (26 papers), Music and Audio Processing (19 papers) and Speech Recognition and Synthesis (14 papers). Emanuele Principi collaborates with scholars based in Italy, United Kingdom and Germany. Emanuele Principi's co-authors include Stefano Squartini, Francesco Piazza, Roberto Bonfigli, Marco Fagiani, Damiano Rossetti, Fabio Vesperini, Marco Severini, Andrea Felicetti, Leonardo Gabrielli and Erik Cambria and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Applied Energy.

In The Last Decade

Emanuele Principi

69 papers receiving 1.1k citations

Author Peers

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

Author Last Decade Papers Cites
Emanuele Principi 482 338 321 248 187 75 1.2k
Daniel Nikovski 458 1.0× 95 0.3× 272 0.8× 526 2.1× 97 0.5× 114 1.2k
Bo Yin 477 1.0× 245 0.7× 315 1.0× 287 1.2× 102 0.5× 126 1.1k
Xin Jin 452 0.9× 61 0.2× 199 0.6× 341 1.4× 98 0.5× 74 1.1k
Farrukh Nagi 472 1.0× 56 0.2× 347 1.1× 347 1.4× 298 1.6× 57 1.4k
Xianlun Tang 505 1.0× 123 0.4× 235 0.7× 243 1.0× 186 1.0× 72 1.3k
Ergun Erçelebi 237 0.5× 310 0.9× 250 0.8× 133 0.5× 343 1.8× 69 1.4k
Raman Paranjape 484 1.0× 87 0.3× 192 0.6× 163 0.7× 364 1.9× 107 1.5k
Chaoyang Jiang 570 1.2× 106 0.3× 223 0.7× 94 0.4× 468 2.5× 45 1.4k
André Eugênio Lazzaretti 392 0.8× 51 0.2× 365 1.1× 274 1.1× 273 1.5× 100 1.1k
Anita Graser 273 0.6× 248 0.7× 109 0.3× 118 0.5× 191 1.0× 72 1.4k

Countries citing papers authored by Emanuele Principi

Since Specialization
Citations

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

Fields of papers citing papers by Emanuele Principi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emanuele Principi

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