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 14
- Advanced Statistical Methods and Models 5
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- Bayesian Methods and Mixture Models 5
- Neural Networks and Applications 2
- Co-authors
- Gareth James (7 shared papers)Jinchi Lv (1 shared paper)Yingying Fan (1 shared paper)David Pollard (1 shared paper)Gourab Mukherjee (2 shared papers)Rahul Mazumder (2 shared papers)Andrey L. Vasnev (2 shared papers)Wendun Wang (1 shared paper)
- Journals
- Journal of Multivariate Analysis (3 papers)Journal of the American Statistical Association (3 papers)The Annals of Statistics (2 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (2 papers)Operations Research (1 paper)
- Partner nations
- United StatesAustraliaNetherlands
In The Last Decade
Peter Radchenko
17 papers receiving 478 citations
Peers
Comparison fields: 5 of 77
- Statistics and Probability 307
- Computational Mathematics 3
- Management Science and Operations Research 54
- Artificial Intelligence 134
- 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-authors
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 | 2008 | 105 | |
| 2 | 2015 | 79 | |
| 3 | 2010 | 66 | |
| 4 | 2008 | 47 | |
| 5 | 2009 | 43 | |
| 6 | 2015 | 36 | |
| 7 | 2011 | 29 | |
| 8 | 2005 | 27 | |
| 9 | 2017 | 16 | |
| 10 | 2022 | 12 | |
| 11 | 2014 | 12 | |
| 12 | MIXED-RATES ASYMPTOTICS | 2013 | 9 |
| 13 | 2021 | 8 | |
| 14 | 2023 | 5 | |
| 15 | 2020 | 3 | |
| 16 | 2017 | 2 | |
| 17 | 2025 | 1 |
About Peter Radchenko
Peter Radchenko is a scholar working on Statistics and Probability, Artificial Intelligence, Computational Mechanics, Control and Systems Engineering and Molecular Biology, having authored 17 papers that have together received 500 indexed citations. Recurring topics across this work include Statistical Methods and Inference (14 papers), Bayesian Methods and Mixture Models (5 papers), Advanced Statistical Methods and Models (5 papers), Sparse and Compressive Sensing Techniques (4 papers), Control Systems and Identification (3 papers), Gene expression and cancer classification (2 papers), Neural Networks and Applications (2 papers) and Financial Risk and Volatility Modeling (2 papers). The work is most often cited by research in Statistics and Probability (307 citations), Computational Mathematics (3 citations), Management Science and Operations Research (54 citations), Artificial Intelligence (134 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 Ellen McDonald. Their work appears in journals such as Journal of Multivariate Analysis, Journal of the American Statistical Association, The Annals of Statistics, Journal of the Royal Statistical Society Series B (Statistical Methodology) 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.