V. Susarla
- Statistics and Probability top 0.5%
- Artificial Intelligence top 5%
- Statistics, Probability and Uncertainty top 2%
- Management Science and Operations Research top 10%
- Economics and Econometrics
- Co-authors
- John Van RyzinHira L. KoulJ. R. BlumJoseph C. GardinerG.G. WalterEswar G. PhadiaAnton SchίckWei‐Yann Tsai
- Topics
- Statistical Methods and Inference (39 papers)Bayesian Methods and Mixture Models (25 papers)Statistical Methods and Bayesian Inference (12 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Statistical AssociationBiometrika
- Partner nations
- United StatesCanada
In The Last Decade
V. Susarla
44 papers receiving 826 citations
Peers
Comparison fields: 5 of 69
- Statistics and Probability 851
- Artificial Intelligence 377
- Statistics, Probability and Uncertainty 108
- Management Science and Operations Research 81
- Economics and Econometrics 46
Countries citing papers authored by V. Susarla
This map shows the geographic impact of V. Susarla'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 V. Susarla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. Susarla more than expected).
Fields of papers citing papers by V. Susarla
This network shows the impact of papers produced by V. Susarla. 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 V. Susarla. The network helps show where V. Susarla may publish in the future.
Co-authorship network of co-authors of V. Susarla
This figure shows the co-authorship network connecting the top 25 collaborators of V. Susarla. A scholar is included among the top collaborators of V. Susarla 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 V. Susarla. V. Susarla 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 | 3 | |
| 3 | 8 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 15 | |
| 7 | 10 | |
| 8 | 7 | |
| 9 | 53 | |
| 10 | 22 | |
| 11 | 5 | |
| 12 | 2 | |
| 13 | 8 | |
| 14 | 13 | |
| 15 | 3 | |
| 16 | Shrinkage Estimation in Nonparametric Bayesian Survival Analysis | 2 |
| 17 | 32 | |
| 18 | 21 | |
| 19 | 8 | |
| 20 | 6 |
About V. Susarla
V. Susarla is a scholar working on Statistics and Probability, Artificial Intelligence and Numerical Analysis, having authored 44 papers that have together received 934 indexed citations. Recurring topics across this work include Statistical Methods and Inference (39 papers), Bayesian Methods and Mixture Models (25 papers) and Statistical Methods and Bayesian Inference (12 papers). The work is most often cited by research in Statistics and Probability (851 citations), Statistics, Probability and Uncertainty (108 citations) and Artificial Intelligence (377 citations). V. Susarla has collaborated with scholars based in United States and Canada. Frequent co-authors include John Van Ryzin, Hira L. Koul, J. R. Blum, Joseph C. Gardiner, G.G. Walter, Eswar G. Phadia, Anton Schίck, Wei‐Yann Tsai, J. K. Ghorai and Richard A. Johnson. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and Biometrika.
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.