Ramesh M. Korwar
- Statistics and Probability top 1%
- Artificial Intelligence top 10%
- Statistics, Probability and Uncertainty top 5%
- Management Science and Operations Research top 10%
- Applied Mathematics top 10%
- Co-authors
- Myles HollanderSubhash C. KocharRam C. DahiyaR. J. SerflingAndrew L. RukhinConstantine Gatsonis
- Topics
- Statistical Distribution Estimation and Applications (12 papers)Bayesian Methods and Mixture Models (11 papers)Statistical Methods and Inference (8 papers)
- Journals
- Journal of the American Statistical AssociationThe Annals of StatisticsThe Annals of Probability
- Partner nations
- United StatesIndia
In The Last Decade
Ramesh M. Korwar
20 papers receiving 317 citations
Peers
Comparison fields: 5 of 48
- Statistics and Probability 265
- Artificial Intelligence 189
- Statistics, Probability and Uncertainty 56
- Management Science and Operations Research 51
- Applied Mathematics 33
Countries citing papers authored by Ramesh M. Korwar
This map shows the geographic impact of Ramesh M. Korwar'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 Ramesh M. Korwar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramesh M. Korwar more than expected).
Fields of papers citing papers by Ramesh M. Korwar
This network shows the impact of papers produced by Ramesh M. Korwar. 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 Ramesh M. Korwar. The network helps show where Ramesh M. Korwar may publish in the future.
Co-authorship network of co-authors of Ramesh M. Korwar
This figure shows the co-authorship network connecting the top 25 collaborators of Ramesh M. Korwar. A scholar is included among the top collaborators of Ramesh M. Korwar 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 Ramesh M. Korwar. Ramesh M. Korwar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 30 | |
| 3 | 5 | |
| 4 | 49 | |
| 5 | 14 | |
| 6 | 0 | |
| 7 | 7 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 5 | |
| 11 | 1 | |
| 12 | 11 | |
| 13 | 9 | |
| 14 | 4 | |
| 15 | 19 | |
| 16 | 7 | |
| 17 | 21 | |
| 18 | 6 | |
| 19 | 119 | |
| 20 | 8 |
About Ramesh M. Korwar
Ramesh M. Korwar is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 21 papers that have together received 342 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (12 papers), Bayesian Methods and Mixture Models (11 papers) and Statistical Methods and Inference (8 papers). The work is most often cited by research in Statistics and Probability (265 citations), Statistics, Probability and Uncertainty (56 citations) and Artificial Intelligence (189 citations). Ramesh M. Korwar has collaborated with scholars based in United States and India. Frequent co-authors include Myles Hollander, Subhash C. Kochar, Ram C. Dahiya, R. J. Serfling, Andrew L. Rukhin and Constantine Gatsonis. Their work appears in journals such as Journal of the American Statistical Association, The Annals of Statistics and The Annals of Probability.
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.