Stefano Di Matteo
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Hardware and Architecture top 5%
- Information Systems top 10%
- Electrical and Electronic Engineering
- Co-authors
- Sergio SaponaraLuca FanucciPietro NannipieriFrancesco BucchiPierpaolo DiniDaniele RossiGuido MaseraMaurizio Martina
- Topics
- Cryptographic Implementations and Security (13 papers)Chaos-based Image/Signal Encryption (8 papers)Physical Unclonable Functions (PUFs) and Hardware Security (7 papers)
In The Last Decade
Stefano Di Matteo
18 papers receiving 271 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 168
- Computer Vision and Pattern Recognition 105
- Hardware and Architecture 101
- Information Systems 62
- Electrical and Electronic Engineering 52
Countries citing papers authored by Stefano Di Matteo
This map shows the geographic impact of Stefano Di Matteo'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 Stefano Di Matteo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Di Matteo more than expected).
Fields of papers citing papers by Stefano Di Matteo
This network shows the impact of papers produced by Stefano Di Matteo. 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 Stefano Di Matteo. The network helps show where Stefano Di Matteo may publish in the future.
Co-authorship network of co-authors of Stefano Di Matteo
This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Di Matteo. A scholar is included among the top collaborators of Stefano Di Matteo 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 Stefano Di Matteo. Stefano Di Matteo 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 | 2 | |
| 3 | 0 | |
| 4 | 16 | |
| 5 | 1 | |
| 6 | 14 | |
| 7 | 21 | |
| 8 | 1 | |
| 9 | 13 | |
| 10 | 14 | |
| 11 | 1 | |
| 12 | 13 | |
| 13 | 12 | |
| 14 | 40 | |
| 15 | 31 | |
| 16 | 19 | |
| 17 | 41 | |
| 18 | 21 | |
| 19 | 11 | |
| 20 | 6 |
About Stefano Di Matteo
Stefano Di Matteo is a scholar working on Hardware and Architecture, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 277 indexed citations. Recurring topics across this work include Cryptographic Implementations and Security (13 papers), Chaos-based Image/Signal Encryption (8 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (7 papers). The work is most often cited by research in Hardware and Architecture (101 citations), Artificial Intelligence (168 citations) and Computer Vision and Pattern Recognition (105 citations). Stefano Di Matteo has collaborated with scholars based in Italy, France and Greece. Frequent co-authors include Sergio Saponara, Luca Fanucci, Pietro Nannipieri, Francesco Bucchi, Pierpaolo Dini, Daniele Rossi, Guido Masera, Maurizio Martina, Pericle Perazzo and Gianluca Dini. Their work appears in journals such as IEEE Access, IEEE Transactions on Computers and Energies.
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.