Francesco Gullo
About
In The Last Decade
Francesco Gullo
60 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 104
- Artificial Intelligence 593
- Statistical and Nonlinear Physics 488
- Signal Processing 301
- Computer Vision and Pattern Recognition 291
- Computer Networks and Communications 266
Countries citing papers authored by Francesco Gullo
This map shows the geographic impact of Francesco Gullo'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 Francesco Gullo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Gullo more than expected).
Fields of papers citing papers by Francesco Gullo
This network shows the impact of papers produced by Francesco Gullo. 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 Francesco Gullo. The network helps show where Francesco Gullo may publish in the future.
Co-authorship network of co-authors of Francesco Gullo
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Gullo. A scholar is included among the top collaborators of Francesco Gullo 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 Francesco Gullo. Francesco Gullo 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 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 27 | |
| 7 | 11 | |
| 8 | 3 | |
| 9 | 57 | |
| 10 | 23 | |
| 11 | 4 | |
| 12 | 4 | |
| 13 | 15 | |
| 14 | 7 | |
| 15 | 3 | |
| 16 | 26 | |
| 17 | 11 | |
| 18 | 2 | |
| 19 | 24 | |
| 20 | Accurate and Fast Similarity Detection in Time Series. | 1 |
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.