Michele Ianni
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Signal Processing top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Giancarlo FortinoAntonella GuzzoDiletta ChiaroPian QiFrancesco PiccialliElio MasciariCarlo ZanioloGiuseppe M. Mazzeo
- Topics
- Advanced Malware Detection Techniques (14 papers)Anomaly Detection Techniques and Applications (8 papers)Network Security and Intrusion Detection (7 papers)
- Partner nations
- ItalyUnited StatesSaudi Arabia
In The Last Decade
Michele Ianni
30 papers receiving 406 citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 279
- Computer Networks and Communications 100
- Information Systems 66
- Signal Processing 54
- Computer Vision and Pattern Recognition 51
Countries citing papers authored by Michele Ianni
This map shows the geographic impact of Michele Ianni'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 Ianni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michele Ianni more than expected).
Fields of papers citing papers by Michele Ianni
This network shows the impact of papers produced by Michele Ianni. 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 Ianni. The network helps show where Michele Ianni may publish in the future.
Co-authorship network of co-authors of Michele Ianni
This figure shows the co-authorship network connecting the top 25 collaborators of Michele Ianni. A scholar is included among the top collaborators of Michele Ianni 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 Ianni. Michele Ianni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 38 | |
| 11 | Model aggregation techniques in federated learning: A comprehensive surveybreakdown → | 167 |
| 12 | 4 | |
| 13 | 3 | |
| 14 | 25 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | 37 | |
| 18 | 2 | |
| 19 | 2 | |
| 20 | 0 |
About Michele Ianni
Michele Ianni is a scholar working on Signal Processing, Artificial Intelligence and Health Informatics, having authored 36 papers that have together received 420 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (14 papers), Anomaly Detection Techniques and Applications (8 papers) and Network Security and Intrusion Detection (7 papers). The work is most often cited by research in Artificial Intelligence (279 citations), Health Informatics (11 citations) and Signal Processing (54 citations). Michele Ianni has collaborated with scholars based in Italy, United States and Saudi Arabia. Frequent co-authors include Giancarlo Fortino, Antonella Guzzo, Diletta Chiaro, Pian Qi, Francesco Piccialli, Elio Masciari, Carlo Zaniolo, Giuseppe M. Mazzeo, Giancarlo Sperlí and Mohammad Mehedi Hassan. Their work appears in journals such as Information Sciences, Information Fusion and Future Generation Computer 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.