Flavio Chierichetti
- Artificial Intelligence top 5%
- Statistical and Nonlinear Physics top 2%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Co-authors
- Alessandro PanconesiSilvio LattanziRavi KumarPrabhakar RaghavanMichael MitzenmacherAndrew TomkinsSergei VassilvitskiiTamás Sarlós
- Topics
- Complex Network Analysis Techniques (17 papers)Caching and Content Delivery (10 papers)Algorithms and Data Compression (9 papers)
- Partner nations
- United StatesItalyIndia
In The Last Decade
Flavio Chierichetti
52 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 449
- Statistical and Nonlinear Physics 419
- Computer Networks and Communications 395
- Computer Vision and Pattern Recognition 307
- Information Systems 193
Countries citing papers authored by Flavio Chierichetti
This map shows the geographic impact of Flavio Chierichetti'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 Flavio Chierichetti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Flavio Chierichetti more than expected).
Fields of papers citing papers by Flavio Chierichetti
This network shows the impact of papers produced by Flavio Chierichetti. 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 Flavio Chierichetti. The network helps show where Flavio Chierichetti may publish in the future.
Co-authorship network of co-authors of Flavio Chierichetti
This figure shows the co-authorship network connecting the top 25 collaborators of Flavio Chierichetti. A scholar is included among the top collaborators of Flavio Chierichetti 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 Flavio Chierichetti. Flavio Chierichetti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Online Facility Location with Multiple Advice | 1 |
| 2 | 2 | |
| 3 | 7 | |
| 4 | 6 | |
| 5 | Algorithms for ℓp Low Rank Approximation | 1 |
| 6 | 2 | |
| 7 | 7 | |
| 8 | 4 | |
| 9 | 7 | |
| 10 | 5 | |
| 11 | 6 | |
| 12 | 75 | |
| 13 | Reconstructing Patterns of Information Diffusion from Incomplete Observations | 11 |
| 14 | 16 | |
| 15 | 2 | |
| 16 | 28 | |
| 17 | 94 | |
| 18 | 54 | |
| 19 | 9 | |
| 20 | 65 |
About Flavio Chierichetti
Flavio Chierichetti is a scholar working on Statistical and Nonlinear Physics, General Decision Sciences and Artificial Intelligence, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (17 papers), Caching and Content Delivery (10 papers) and Algorithms and Data Compression (9 papers). The work is most often cited by research in Statistical and Nonlinear Physics (419 citations), Computer Networks and Communications (395 citations) and Signal Processing (162 citations). Flavio Chierichetti has collaborated with scholars based in United States, Italy and India. Frequent co-authors include Alessandro Panconesi, Silvio Lattanzi, Ravi Kumar, Prabhakar Raghavan, Michael Mitzenmacher, Ravi Kumar, Andrew Tomkins, Sergei Vassilvitskii, Tamás Sarlós and Jon Kleinberg. Their work appears in journals such as IEEE Transactions on Information Theory, Journal of the ACM and SIAM Journal on 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.