Marco Picone
Impact in
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- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Energy Efficient Wireless Sensor Networks
- Opportunistic and Delay-Tolerant Networks
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- Digital Transformation in Industry
Papers in
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- IoT and Edge/Fog Computing 33
- Caching and Content Delivery 12
- Opportunistic and Delay-Tolerant Networks 12
- Peer-to-Peer Network Technologies 11
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- Digital Transformation in Industry 35
- Flexible and Reconfigurable Manufacturing Systems 7
- Co-authors
- Simone Cirani (20 shared papers)Gianluigi Ferrari (18 shared papers)Luca Veltri (10 shared papers)Marco Mamei (28 shared papers)Michele Amoretti (22 shared papers)Francesco Zanichelli (19 shared papers)Carlo Giannelli (9 shared papers)Paolo Bellavista (7 shared papers)
In The Last Decade
Marco Picone
85 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 101
- Computer Networks and Communications 873
- Industrial and Manufacturing Engineering 321
- Information Systems 439
- Signal Processing 118
- Computer Vision and Pattern Recognition 161
Countries citing papers authored by Marco Picone
This map shows the geographic impact of Marco Picone'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 Marco Picone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Picone more than expected).
Fields of papers citing papers by Marco Picone
This network shows the impact of papers produced by Marco Picone. 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 Marco Picone. The network helps show where Marco Picone may publish in the future.
Co-authors
The 25 scholars most cited alongside Marco Picone, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 165 | |
| 2 | 2014 | 160 | |
| 3 | 2021 | 100 | |
| 4 | 2012 | 97 | |
| 5 | 2022 | 63 | |
| 6 | 2015 | 58 | |
| 7 | 2023 | 53 | |
| 8 | 2014 | 45 | |
| 9 | 2015 | 45 | |
| 10 | 2021 | 40 | |
| 11 | 2022 | 35 | |
| 12 | 2015 | 32 | |
| 13 | 2013 | 31 | |
| 14 | 2014 | 28 | |
| 15 | 2014 | 27 | |
| 16 | 2014 | 24 | |
| 17 | 2018 | 23 | |
| 18 | 2018 | 22 | |
| 19 | 2013 | 21 | |
| 20 | 2010 | 20 |
About Marco Picone
Marco Picone is a scholar working on Computer Networks and Communications, Industrial and Manufacturing Engineering, Information Systems, Electrical and Electronic Engineering and Artificial Intelligence, having authored 98 papers that have together received 1.5k indexed citations. Recurring topics across this work include Digital Transformation in Industry (35 papers), IoT and Edge/Fog Computing (33 papers), Blockchain Technology Applications and Security (12 papers), Caching and Content Delivery (12 papers), Opportunistic and Delay-Tolerant Networks (12 papers), Peer-to-Peer Network Technologies (11 papers), Cloud Computing and Resource Management (7 papers) and Flexible and Reconfigurable Manufacturing Systems (7 papers). The work is most often cited by research in Computer Networks and Communications (873 citations), Industrial and Manufacturing Engineering (321 citations), Information Systems (439 citations), Signal Processing (118 citations) and Computer Vision and Pattern Recognition (161 citations). Marco Picone has collaborated with scholars based in Italy, France and Germany. Frequent co-authors include Simone Cirani, Gianluigi Ferrari, Luca Veltri, Marco Mamei, Michele Amoretti, Francesco Zanichelli, Carlo Giannelli, Paolo Bellavista, Luca Davoli and Franco Zambonelli. Their work appears in journals such as Future Generation Computer Systems, Pervasive and Mobile Computing, Computers in Industry, Future Internet and IEEE Internet Computing.
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.