Leonardo Reyneri

226 total papers · 1.7k total citations
130 papers, 1.1k citations indexed

About

Leonardo Reyneri is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Leonardo Reyneri has authored 130 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Electrical and Electronic Engineering, 43 papers in Artificial Intelligence and 31 papers in Aerospace Engineering. Recurrent topics in Leonardo Reyneri's work include Neural Networks and Applications (39 papers), Spacecraft Design and Technology (27 papers) and Fuzzy Logic and Control Systems (20 papers). Leonardo Reyneri is often cited by papers focused on Neural Networks and Applications (39 papers), Spacecraft Design and Technology (27 papers) and Fuzzy Logic and Control Systems (20 papers). Leonardo Reyneri collaborates with scholars based in Italy, Pakistan and Spain. Leonardo Reyneri's co-authors include Stefano Di Pascoli, Marcello Chiaberge, Muhammad Rizwan Mughal, Anwar Ali, Dante Del Corso, E. Filippi, Haider Ali, Valentina Colla, Francesco Gregoretti and Claudio Passerone and has published in prestigious journals such as IEEE Access, IEEE Journal of Solid-State Circuits and IEEE Transactions on Industry Applications.

In The Last Decade

Leonardo Reyneri

118 papers receiving 996 citations

Author Peers

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

Author Last Decade Papers Cites
Leonardo Reyneri 559 340 220 197 156 130 1.1k
Ricardo Martins 896 1.6× 169 0.5× 125 0.6× 352 1.8× 79 0.5× 115 1.4k
Abdul Quaiyum Ansari 651 1.2× 169 0.5× 313 1.4× 52 0.3× 163 1.0× 133 1.5k
Houjun Wang 635 1.1× 194 0.6× 78 0.4× 205 1.0× 448 2.9× 195 1.5k
Yinan Li 396 0.7× 158 0.5× 79 0.4× 186 0.9× 266 1.7× 91 1.2k
Yigang He 826 1.5× 195 0.6× 53 0.2× 298 1.5× 463 3.0× 93 1.3k
Xuan Zhang 782 1.4× 280 0.8× 68 0.3× 252 1.3× 52 0.3× 89 1.3k
Giovanni Beltrame 364 0.7× 182 0.5× 287 1.3× 289 1.5× 124 0.8× 128 1.3k
Tianming Ni 852 1.5× 143 0.4× 43 0.2× 316 1.6× 56 0.4× 109 1.3k
Jorge Cabral 632 1.1× 189 0.6× 112 0.5× 133 0.7× 71 0.5× 121 1.4k
B.S. Heck 317 0.6× 99 0.3× 107 0.5× 117 0.6× 560 3.6× 79 1.2k

Countries citing papers authored by Leonardo Reyneri

Since Specialization
Citations

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

Fields of papers citing papers by Leonardo Reyneri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonardo Reyneri

This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo Reyneri. A scholar is included among the top collaborators of Leonardo Reyneri 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 Leonardo Reyneri. Leonardo Reyneri 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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2026