Michele De Donno

25 total papers · 1.2k total citations
17 papers, 793 citations indexed

About

Michele De Donno is a scholar working on Computer Networks and Communications, Information Systems and Signal Processing. According to data from OpenAlex, Michele De Donno has authored 17 papers receiving a total of 793 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Networks and Communications, 6 papers in Information Systems and 6 papers in Signal Processing. Recurrent topics in Michele De Donno's work include IoT and Edge/Fog Computing (11 papers), Network Security and Intrusion Detection (8 papers) and Advanced Malware Detection Techniques (6 papers). Michele De Donno is often cited by papers focused on IoT and Edge/Fog Computing (11 papers), Network Security and Intrusion Detection (8 papers) and Advanced Malware Detection Techniques (6 papers). Michele De Donno collaborates with scholars based in Denmark, Sweden and Italy. Michele De Donno's co-authors include Nicola Dragoni, Koen Tange, Xenofon Fafoutis, Alberto Giaretta, Angelo Spognardi, Manuel Mazzara, Antonio Bucchiarone, Martin Nordal Petersen, Michael Berger and Sarah Ruepp and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, IEEE Access and Future Internet.

In The Last Decade

Michele De Donno

17 papers receiving 758 citations

Hit Papers

A Systematic Survey of In... 2020 2026 2022 2024 2020 50 100 150 200 250

Author Peers

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

Author Last Decade Papers Cites
Michele De Donno 582 288 210 207 131 17 793
Fadele Ayotunde Alaba 621 1.1× 361 1.3× 205 1.0× 210 1.0× 114 0.9× 9 856
Caifeng Zou 530 0.9× 254 0.9× 161 0.8× 145 0.7× 183 1.4× 13 864
Pablo Nájera 541 0.9× 273 0.9× 170 0.8× 142 0.7× 133 1.0× 25 898
Mahmoud Ammar 471 0.8× 290 1.0× 244 1.2× 237 1.1× 145 1.1× 37 775
Yizhen Jia 500 0.9× 203 0.7× 298 1.4× 236 1.1× 102 0.8× 12 674
Ziaur Rahman 418 0.7× 237 0.8× 253 1.2× 113 0.5× 161 1.2× 37 768
Arsalan Mosenia 468 0.8× 274 1.0× 162 0.8× 242 1.2× 127 1.0× 12 755
Nataliia Neshenko 449 0.8× 240 0.8× 237 1.1× 254 1.2× 106 0.8× 12 666
T. Andrew Yang 423 0.7× 252 0.9× 156 0.7× 133 0.6× 137 1.0× 31 630
Shahid Khan 628 1.1× 275 1.0× 114 0.5× 129 0.6× 252 1.9× 9 904

Countries citing papers authored by Michele De Donno

Since Specialization
Citations

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

Fields of papers citing papers by Michele De Donno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michele De Donno. 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 Michele De Donno. The network helps show where Michele De Donno may publish in the future.

Co-authorship network of co-authors of Michele De Donno

This figure shows the co-authorship network connecting the top 25 collaborators of Michele De Donno. A scholar is included among the top collaborators of Michele De Donno 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 Michele De Donno. Michele De Donno 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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