Ambra Demontis

25 papers and 765 indexed citations i.

About

Ambra Demontis is a scholar working on Artificial Intelligence, Signal Processing and Molecular Biology. According to data from OpenAlex, Ambra Demontis has authored 25 papers receiving a total of 765 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 12 papers in Signal Processing and 3 papers in Molecular Biology. Recurrent topics in Ambra Demontis’s work include Adversarial Robustness in Machine Learning (22 papers), Advanced Malware Detection Techniques (11 papers) and Anomaly Detection Techniques and Applications (11 papers). Ambra Demontis is often cited by papers focused on Adversarial Robustness in Machine Learning (22 papers), Advanced Malware Detection Techniques (11 papers) and Anomaly Detection Techniques and Applications (11 papers). Ambra Demontis collaborates with scholars based in Italy, China and Germany. Ambra Demontis's co-authors include Battista Biggio, Fabio Roli, Davide Maiorca, Giorgio Giacinto, Marco Melis, Emil Lupu, Andrea Paudice, Luis Muñoz-González, Claudia Eckert and Bojan Kolosnjaji and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Information Sciences and ACM Computing Surveys.

In The Last Decade

Co-authorship network of co-authors of Ambra Demontis i

Fields of papers citing papers by Ambra Demontis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Ambra Demontis

Since Specialization
Citations

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

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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2025