Nicola Bicocchi
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Transportation top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Co-authors
- Marco MameiFranco ZambonelliGiacomo CabriMassimo MecellaCarlo GiannelliFederica MandreoliMarco PiconePaolo Bellavista
- Topics
- Context-Aware Activity Recognition Systems (19 papers)Modular Robots and Swarm Intelligence (9 papers)Digital Transformation in Industry (9 papers)
- Partner nations
- ItalyUnited KingdomGermany
In The Last Decade
Nicola Bicocchi
47 papers receiving 578 citations
Peers
Comparison fields: 5 of 81
- Computer Networks and Communications 163
- Artificial Intelligence 143
- Transportation 113
- Computer Vision and Pattern Recognition 105
- Information Systems 98
Countries citing papers authored by Nicola Bicocchi
This map shows the geographic impact of Nicola Bicocchi'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 Nicola Bicocchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicola Bicocchi more than expected).
Fields of papers citing papers by Nicola Bicocchi
This network shows the impact of papers produced by Nicola Bicocchi. 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 Nicola Bicocchi. The network helps show where Nicola Bicocchi may publish in the future.
Co-authorship network of co-authors of Nicola Bicocchi
This figure shows the co-authorship network connecting the top 25 collaborators of Nicola Bicocchi. A scholar is included among the top collaborators of Nicola Bicocchi 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 Nicola Bicocchi. Nicola Bicocchi 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 | 11 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 48 | |
| 8 | 1 | |
| 9 | 32 | |
| 10 | 4 | |
| 11 | 5 | |
| 12 | 1 | |
| 13 | 49 | |
| 14 | 2 | |
| 15 | 16 | |
| 16 | 36 | |
| 17 | 0 | |
| 18 | 2 | |
| 19 | 10 | |
| 20 | Towards Self-Organizing Knowledge Networks for Smart World Infrastructures | 12 |
About Nicola Bicocchi
Nicola Bicocchi is a scholar working on Transportation, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 52 papers that have together received 595 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (19 papers), Modular Robots and Swarm Intelligence (9 papers) and Digital Transformation in Industry (9 papers). The work is most often cited by research in Transportation (113 citations), Industrial and Manufacturing Engineering (87 citations) and Computer Networks and Communications (163 citations). Nicola Bicocchi has collaborated with scholars based in Italy, United Kingdom and Germany. Frequent co-authors include Marco Mamei, Franco Zambonelli, Giacomo Cabri, Massimo Mecella, Carlo Giannelli, Federica Mandreoli, Marco Picone, Paolo Bellavista, Gabriella Castelli and Alberto Rosi. Their work appears in journals such as Sensors, IEEE Transactions on Intelligent Transportation Systems and Géotechnique.
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.