Edoardo Serra

66 papers receiving 536 citations

Peers

Edoardo Serra
Comparison fields: 5 of 82
  • Signal Processing 142
  • Computer Networks and Communications 293
  • Information Systems 206
  • Artificial Intelligence 233
  • Computer Vision and Pattern Recognition 67
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Simone Raponi Qatar
Chunhe Xia China
D. P. Zegzhda Russia
Yu Jin United States
Chin‐Tser Huang United States
Christoph F. Eick United States
Aaisha Makkar India
Lisa Amini United States
Glenn Fink United States
Aibo Song China
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Citations per year

Countries citing papers authored by Edoardo Serra

Since Specialization
Citations

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

Fields of papers citing papers by Edoardo Serra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Edoardo Serra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Edoardo Serra Line = papers co-authored together Edoardo Serra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201528
2 201727
3 201226
4 201624
5 202023
6 202123
7 201922
8 201522
9 201721
10 202019
11 201418
12 201915
13 200914
14 202114
15 201914
16 202013
17 201413
18 201812
19 201312
20 202112

About Edoardo Serra

Edoardo Serra is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Signal Processing and Sociology and Political Science, having authored 71 papers that have together received 548 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (21 papers), Advanced Malware Detection Techniques (11 papers), Complex Network Analysis Techniques (9 papers), Information and Cyber Security (8 papers), Anomaly Detection Techniques and Applications (8 papers), Spam and Phishing Detection (7 papers), Advanced Graph Neural Networks (7 papers) and Imbalanced Data Classification Techniques (6 papers). The work is most often cited by research in Signal Processing (142 citations), Computer Networks and Communications (293 citations), Information Systems (206 citations), Artificial Intelligence (233 citations) and Computer Vision and Pattern Recognition (67 citations). Edoardo Serra has collaborated with scholars based in United States, Italy and France. Frequent co-authors include V. S. Subrahmanian, Antonino Rullo, Francesca Spezzano, Noseong Park, Sushil Jajodia, Carlo Zaniolo, Alfredo Cuzzocrea, Dianxiang Xu, Elisa Bertino and Andrea Pugliese. Their work appears in journals such as Journal of Computer Security, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Data Mining and Knowledge Discovery, IEEE Intelligent Systems and IEEE Transactions on Computational Social Systems.

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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