Sourav Chatterjee
- Statistics and Probability top 0.5%
- Random Matrices and Applications 18
- Markov Chains and Monte Carlo Methods 6
- Mathematical Physics top 2%
- Stochastic processes and statistical mechanics 24
- Mathematical Dynamics and Fractals 4
- Advanced Algebra and Geometry 3
- Geometry and Topology top 5%
- Graph theory and applications 4
- Applied Mathematics top 5%
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- Theoretical and Computational Physics 11
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- Sparse and Compressive Sensing Techniques 4
- Co-authors
- S. R. S. VaradhanJoshua BlumenstockHan FangGuanghua ChiSoumik PalEthan AnderesArup BoseDan Romik
- Journals
- Proceedings of the National Academy of Sciences (1 paper)IEEE Transactions on Information Theory (1 paper)The Annals of Statistics (3 papers)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Sourav Chatterjee
43 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 107
- Statistics and Probability 559
- Discrete Mathematics and Combinatorics 205
- Mathematical Physics 421
- Geometry and Topology 156
- Applied Mathematics 163
Countries citing papers authored by Sourav Chatterjee
This map shows the geographic impact of Sourav Chatterjee'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 Sourav Chatterjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sourav Chatterjee more than expected).
Fields of papers citing papers by Sourav Chatterjee
This network shows the impact of papers produced by Sourav Chatterjee. 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 Sourav Chatterjee. The network helps show where Sourav Chatterjee may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Sourav Chatterjee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 1 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 5 | |
| 11 | 2022 | 4 | |
| 12 | 2021 | 4 | |
| 13 | 2019 | 4 | |
| 14 | 2017 | 0 | |
| 15 | 2014 | 33 | |
| 16 | 2011 | 95 | |
| 17 | Stein's Method of Exchangeable Pairs with Application to the Curie-Weiss Model | 2009 | 4 |
| 18 | 2008 | 78 | |
| 19 | 2007 | 10 | |
| 20 | 2006 | 72 |
About Sourav Chatterjee
Sourav Chatterjee is a scholar working on Mathematical Physics, Statistics and Probability and Discrete Mathematics and Combinatorics, having authored 46 papers that have together received 1.2k indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (24 papers), Random Matrices and Applications (18 papers), Theoretical and Computational Physics (11 papers), Markov Chains and Monte Carlo Methods (6 papers), Graph theory and applications (4 papers), Sparse and Compressive Sensing Techniques (4 papers), Mathematical Dynamics and Fractals (4 papers) and Advanced Algebra and Geometry (3 papers). The work is most often cited by research in Statistics and Probability (559 citations), Discrete Mathematics and Combinatorics (205 citations) and Mathematical Physics (421 citations). Sourav Chatterjee has collaborated with scholars based in United States, India and Canada. Frequent co-authors include S. R. S. Varadhan, Joshua Blumenstock, Han Fang, Guanghua Chi, Soumik Pal, Ethan Anderes, Arup Bose, Dan Romik, Persi Diaconis and Ron Peled. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Information Theory and The Annals of Statistics.
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.