Sabyasachi Chatterjee
- Statistics and Probability top 5%
- Statistical Methods and Inference 8
- Advanced Statistical Methods and Models 4
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- Sparse and Compressive Sensing Techniques 4
- Surface Roughness and Optical Measurements 2
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- Optical measurement and interference techniques 2
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- Machine Learning and Data Classification 2
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- Virus-based gene therapy research 1
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- Herpesvirus Infections and Treatments 1
- Co-authors
- Adityanand GuntuboyinaBodhisattva SenRichard J. WhitleyJunichi KogaRichard J. SamworthTengyao WangAndrew R. BarronYi Yu
- Journals
- The Annals of Statistics (3 papers)Electronic Journal of Statistics (1 paper)Bernoulli (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Sabyasachi Chatterjee
12 papers receiving 179 citations
Peers
Comparison fields: 5 of 62
- Statistics and Probability 111
- Statistics, Probability and Uncertainty 19
- Computational Mechanics 45
- Computational Mathematics 1
- Pharmacology 24
Countries citing papers authored by Sabyasachi Chatterjee
This map shows the geographic impact of Sabyasachi 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 Sabyasachi Chatterjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sabyasachi Chatterjee more than expected).
Fields of papers citing papers by Sabyasachi Chatterjee
This network shows the impact of papers produced by Sabyasachi 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 Sabyasachi Chatterjee. The network helps show where Sabyasachi Chatterjee may publish in the future.
Co-authorship network
The 11 scholars most cited alongside Sabyasachi 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 | 2022 | 7 | |
| 2 | 2020 | 20 | |
| 3 | 2019 | 32 | |
| 4 | Prediction Rule Reshaping | 2018 | 0 |
| 5 | Spatial Adaptation in Trend Filtering | 2017 | 6 |
| 6 | 2017 | 24 | |
| 7 | 2015 | 55 | |
| 8 | Adaptation in Estimation and Annealing | 2014 | 1 |
| 9 | 2014 | 5 | |
| 10 | Improved Risk Bounds in Isotonic Regression | 2013 | 4 |
| 11 | 2013 | 4 | |
| 12 | 2004 | 5 | |
| 13 | 1993 | 37 |
About Sabyasachi Chatterjee
Sabyasachi Chatterjee is a scholar working on Statistics and Probability, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 13 papers that have together received 200 indexed citations. Recurring topics across this work include Statistical Methods and Inference (8 papers), Sparse and Compressive Sensing Techniques (4 papers), Advanced Statistical Methods and Models (4 papers), Optical measurement and interference techniques (2 papers), Surface Roughness and Optical Measurements (2 papers), Machine Learning and Data Classification (2 papers), Virus-based gene therapy research (1 paper) and Herpesvirus Infections and Treatments (1 paper). The work is most often cited by research in Statistics and Probability (111 citations), Statistics, Probability and Uncertainty (19 citations) and Computational Mechanics (45 citations). Sabyasachi Chatterjee has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Adityanand Guntuboyina, Bodhisattva Sen, Richard J. Whitley, Junichi Koga, Richard J. Samworth, Tengyao Wang, Andrew R. Barron, Yi Yu, Ravinder K. Banyal and Rina Foygel Barber. Their work appears in journals such as The Annals of Statistics, Electronic Journal of Statistics, Bernoulli, Applied Optics and Antiviral 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.