Pavel Chebotarev
- Statistical and Nonlinear Physics top 2%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 5%
- Geometry and Topology top 5%
- Co-authors
- Elena ShamisRafig AgaevKonstantin AvrachenkovVictor KozyakinElena DezaFederico Martín IbáñezR.B. BapatDmitry Gubanov
- Topics
- Graph theory and applications (14 papers)Opinion Dynamics and Social Influence (8 papers)Complex Network Analysis Techniques (7 papers)
In The Last Decade
Pavel Chebotarev
36 papers receiving 626 citations
Peers
Comparison fields: 5 of 85
- Statistical and Nonlinear Physics 252
- Computer Networks and Communications 168
- Artificial Intelligence 156
- Computational Theory and Mathematics 138
- Geometry and Topology 130
Countries citing papers authored by Pavel Chebotarev
This map shows the geographic impact of Pavel Chebotarev'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 Pavel Chebotarev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavel Chebotarev more than expected).
Fields of papers citing papers by Pavel Chebotarev
This network shows the impact of papers produced by Pavel Chebotarev. 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 Pavel Chebotarev. The network helps show where Pavel Chebotarev may publish in the future.
Co-authorship network of co-authors of Pavel Chebotarev
This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Chebotarev. A scholar is included among the top collaborators of Pavel Chebotarev 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 Pavel Chebotarev. Pavel Chebotarev 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 | 4 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 12 | |
| 8 | 1 | |
| 9 | 19 | |
| 10 | 11 | |
| 11 | 40 | |
| 12 | 7 | |
| 13 | A New Family of Graph Distances | 2 |
| 14 | 24 | |
| 15 | On Proximity Measures for Graph Vertices | 34 |
| 16 | 5 | |
| 17 | 5 | |
| 18 | 127 | |
| 19 | 34 | |
| 20 | THE MATRIX-FOREST THEOREM AND MEASURING RELATIONS IN SMALL SOCIAL GROUPS | 111 |
About Pavel Chebotarev
Pavel Chebotarev is a scholar working on Computational Mathematics, Geometry and Topology and Statistical and Nonlinear Physics, having authored 41 papers that have together received 648 indexed citations. Recurring topics across this work include Graph theory and applications (14 papers), Opinion Dynamics and Social Influence (8 papers) and Complex Network Analysis Techniques (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (252 citations), Geometry and Topology (130 citations) and Computational Theory and Mathematics (138 citations). Pavel Chebotarev has collaborated with scholars based in Russia, Israel and India. Frequent co-authors include Elena Shamis, Rafig Agaev, Konstantin Avrachenkov, Victor Kozyakin, Elena Deza, Federico Martín Ibáñez, R.B. Bapat, Dmitry Gubanov, Pavel Shcherbakov and Sergei Parsegov. Their work appears in journals such as Proceedings of the IEEE, IEEE Transactions on Systems Man and Cybernetics Systems and Annals of Operations Research.
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.