Andrea Paudice

851 total citations · 1 hit paper
5 papers, 336 citations indexed

About

Andrea Paudice is a scholar working on Computer Networks and Communications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Andrea Paudice has authored 5 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Networks and Communications, 2 papers in Information Systems and 2 papers in Artificial Intelligence. Recurrent topics in Andrea Paudice's work include Network Security and Intrusion Detection (5 papers), Software System Performance and Reliability (3 papers) and Information and Cyber Security (2 papers). Andrea Paudice is often cited by papers focused on Network Security and Intrusion Detection (5 papers), Software System Performance and Reliability (3 papers) and Information and Cyber Security (2 papers). Andrea Paudice collaborates with scholars based in Italy, United Kingdom and India. Andrea Paudice's co-authors include Luis Muñoz-González, Emil Lupu, Fabio Roli, Battista Biggio, Ambra Demontis, Domenico Cotroneo, Antonio Pecchia and Santonu Sarkar and has published in prestigious journals such as Future Generation Computer Systems, IEEE Transactions on Dependable and Secure Computing and ACM Transactions on Sensor Networks.

In The Last Decade

Andrea Paudice

5 papers receiving 319 citations

Hit Papers

Towards poisoning of deep learning algorithms with back-g... 2017 2026 2020 2023 2017 50 100 150 200 250

Peers

Andrea Paudice
Comparison fields: 5 of 48
  • Artificial Intelligence 276
  • Computer Networks and Communications 95
  • Signal Processing 89
  • Information Systems 47
  • Computer Vision and Pattern Recognition 31
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Citations per field, relative to Andrea Paudice
Andrea Paudice · 1×
Citations per year, relative to Andrea Paudice
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Countries citing papers authored by Andrea Paudice

Since Specialization
Citations

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

Fields of papers citing papers by Andrea Paudice

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Paudice

This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Paudice. A scholar is included among the top collaborators of Andrea Paudice 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 Andrea Paudice. Andrea Paudice is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
# Work Indexed citations
1 11
2 14
3
Towards poisoning of deep learning algorithms with back-gradient optimization breakdown →
287
4 23
5 1

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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