Eitan Greenshtein
- Statistics and Probability top 2%
- Artificial Intelligence top 10%
- Computational Mechanics
- Management Science and Operations Research top 10%
- Statistics, Probability and Uncertainty top 10%
- Co-authors
- Ya’acov RitovLawrence D. BrownGad RabinowitzIsrael DavidGuy LebanonErik TorgersenEphraim KorachAlexander Goldenshluger
- Topics
- Statistical Methods and Inference (12 papers)Advanced Statistical Process Monitoring (12 papers)Statistical Methods in Clinical Trials (7 papers)
- Journals
- Journal of the American Statistical AssociationThe Annals of StatisticsJournal of Machine Learning Research
- Partner nations
- IsraelUnited StatesNorway
In The Last Decade
Eitan Greenshtein
23 papers receiving 301 citations
Peers
Comparison fields: 5 of 63
- Statistics and Probability 231
- Artificial Intelligence 117
- Computational Mechanics 55
- Management Science and Operations Research 39
- Statistics, Probability and Uncertainty 33
Countries citing papers authored by Eitan Greenshtein
This map shows the geographic impact of Eitan Greenshtein'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 Eitan Greenshtein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eitan Greenshtein more than expected).
Fields of papers citing papers by Eitan Greenshtein
This network shows the impact of papers produced by Eitan Greenshtein. 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 Eitan Greenshtein. The network helps show where Eitan Greenshtein may publish in the future.
Co-authorship network of co-authors of Eitan Greenshtein
This figure shows the co-authorship network connecting the top 25 collaborators of Eitan Greenshtein. A scholar is included among the top collaborators of Eitan Greenshtein 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 Eitan Greenshtein. Eitan Greenshtein is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 15 | |
| 5 | 1 | |
| 6 | Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification | 13 |
| 7 | 7 | |
| 8 | Non parametric empirical Bayes and compound decision approaches to estimation of a high dimensional vector of normal means | 61 |
| 9 | 171 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 4 | |
| 13 | 0 | |
| 14 | 9 | |
| 15 | 14 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | 2 | |
| 19 | 1 | |
| 20 | 0 |
About Eitan Greenshtein
Eitan Greenshtein is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 26 papers that have together received 337 indexed citations. Recurring topics across this work include Statistical Methods and Inference (12 papers), Advanced Statistical Process Monitoring (12 papers) and Statistical Methods in Clinical Trials (7 papers). The work is most often cited by research in Statistics and Probability (231 citations), Statistics, Probability and Uncertainty (33 citations) and Artificial Intelligence (117 citations). Eitan Greenshtein has collaborated with scholars based in Israel, United States and Norway. Frequent co-authors include Ya’acov Ritov, Lawrence D. Brown, Gad Rabinowitz, Israel David, Guy Lebanon, Erik Torgersen, Ephraim Korach and Alexander Goldenshluger. Their work appears in journals such as Journal of the American Statistical Association, The Annals of Statistics and Journal of Machine Learning 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.