Srabashi Basu
- Endocrinology, Diabetes and Metabolism top 5%
- Statistics and Probability top 2%
- Rehabilitation top 5%
- Surgery
- Artificial Intelligence
- Co-authors
- Daniel F. HeitjanJacqueline A. PughHisham R. AshryLawrence A. LaveryLawrence B. HarklessAyanendranath BasuJ. Richard LandisTapan K. Mukherjee
- Topics
- Statistical Methods and Bayesian Inference (7 papers)Advanced Statistical Methods and Models (6 papers)Statistical Methods and Inference (5 papers)
- Partner nations
- United StatesIndiaHong Kong
In The Last Decade
Srabashi Basu
20 papers receiving 663 citations
Peers
Comparison fields: 5 of 121
- Endocrinology, Diabetes and Metabolism 214
- Statistics and Probability 212
- Rehabilitation 89
- Surgery 77
- Artificial Intelligence 70
Countries citing papers authored by Srabashi Basu
This map shows the geographic impact of Srabashi Basu'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 Srabashi Basu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srabashi Basu more than expected).
Fields of papers citing papers by Srabashi Basu
This network shows the impact of papers produced by Srabashi Basu. 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 Srabashi Basu. The network helps show where Srabashi Basu may publish in the future.
Co-authorship network of co-authors of Srabashi Basu
This figure shows the co-authorship network connecting the top 25 collaborators of Srabashi Basu. A scholar is included among the top collaborators of Srabashi Basu 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 Srabashi Basu. Srabashi Basu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 34 | |
| 2 | 9 | |
| 3 | Parametric models for incubation distribution in presence of left and right censoring | 2 |
| 4 | 9 | |
| 5 | 5 | |
| 6 | 5 | |
| 7 | Exact minimum disparity inference in complex multinomial models | 0 |
| 8 | 8 | |
| 9 | PENALIZED MINIMUM DISPARITY METHODS FOR MULTINOMIAL MODELS | 25 |
| 10 | 26 | |
| 11 | 1 | |
| 12 | 19 | |
| 13 | 161 | |
| 14 | 12 | |
| 15 | 69 | |
| 16 | 8 | |
| 17 | 8 | |
| 18 | 33 | |
| 19 | 1 | |
| 20 | 66 |
About Srabashi Basu
Srabashi Basu is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Transplantation, having authored 21 papers that have together received 705 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (7 papers), Advanced Statistical Methods and Models (6 papers) and Statistical Methods and Inference (5 papers). The work is most often cited by research in Statistics and Probability (212 citations), Occupational Therapy (61 citations) and Rehabilitation (89 citations). Srabashi Basu has collaborated with scholars based in United States, India and Hong Kong. Frequent co-authors include Daniel F. Heitjan, Jacqueline A. Pugh, Hisham R. Ashry, Lawrence A. Lavery, Lawrence B. Harkless, Ayanendranath Basu, J. Richard Landis, Tapan K. Mukherjee, Suvro Banerjee and Chanseok Park. Their work appears in journals such as Diabetes Care, Diabetes and American Journal of Epidemiology.
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.