Peter Radchenko
Impact in
- Statistics and Probability top 1%
- Statistical Methods and Inference
- Advanced Statistical Methods and Models
- Statistical Methods and Bayesian Inference
Papers in
-
- Statistical Methods and Inference 13
- Advanced Statistical Methods and Models 5
- Statistical Methods and Bayesian Inference 1
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- Sparse and Compressive Sensing Techniques 4
- Co-authors
- Gareth JamesJinchi LvYingying FanDavid PollardGourab MukherjeeRahul MazumderAndrey L. VasnevWendun Wang
- Journals
- Journal of Multivariate Analysis (3 papers)Journal of the American Statistical Association (3 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (2 papers)The Annals of Statistics (2 papers)Operations Research (1 paper)
- Partner nations
- United StatesAustraliaNetherlands
In The Last Decade
Peter Radchenko
16 papers receiving 461 citations
Peers
Comparison fields: 5 of 77
- Statistics and Probability 295
- Computational Mathematics 3
- Management Science and Operations Research 53
- Artificial Intelligence 131
- Computational Mechanics 75
Countries citing papers authored by Peter Radchenko
This map shows the geographic impact of Peter Radchenko'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 Peter Radchenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Radchenko more than expected).
Fields of papers citing papers by Peter Radchenko
This network shows the impact of papers produced by Peter Radchenko. 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 Peter Radchenko. The network helps show where Peter Radchenko may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Peter Radchenko, 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 | 2025 | 1 | |
| 2 | 2023 | 5 | |
| 3 | 2022 | 10 | |
| 4 | 2021 | 8 | |
| 5 | 2020 | 3 | |
| 6 | 2017 | 2 | |
| 7 | 2017 | 16 | |
| 8 | 2015 | 35 | |
| 9 | 2015 | 78 | |
| 10 | 2014 | 11 | |
| 11 | 2011 | 29 | |
| 12 | 2010 | 66 | |
| 13 | 2009 | 43 | |
| 14 | 2008 | 46 | |
| 15 | 2008 | 105 | |
| 16 | 2005 | 26 |
About Peter Radchenko
Peter Radchenko is a scholar working on Statistics and Probability, Computational Mechanics, Artificial Intelligence, Statistics, Probability and Uncertainty and Emergency Medical Services, having authored 16 papers that have together received 484 indexed citations. Recurring topics across this work include Statistical Methods and Inference (13 papers), Advanced Statistical Methods and Models (5 papers), Sparse and Compressive Sensing Techniques (4 papers), Bayesian Methods and Mixture Models (4 papers), Control Systems and Identification (3 papers), Neural Networks and Applications (2 papers), Gene expression and cancer classification (2 papers) and Statistical Methods and Bayesian Inference (1 paper). The work is most often cited by research in Statistics and Probability (295 citations), Computational Mathematics (3 citations), Management Science and Operations Research (53 citations), Artificial Intelligence (131 citations) and Computational Mechanics (75 citations). Peter Radchenko has collaborated with scholars based in United States, Australia and Netherlands. Frequent co-authors include Gareth James, Jinchi Lv, Yingying Fan, David Pollard, Gourab Mukherjee, Rahul Mazumder, Andrey L. Vasnev, Wendun Wang, Laurent L. Pauwels and Ross Bailie. Their work appears in journals such as Journal of Multivariate Analysis, Journal of the American Statistical Association, Journal of the Royal Statistical Society Series B (Statistical Methodology), The Annals of Statistics and Operations 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.