Dmitry Panchenko
- Artificial Intelligence top 5%
- Condensed Matter Physics top 5%
- Statistics and Probability top 1%
- Mathematical Physics top 5%
- Computational Theory and Mathematics top 5%
- Co-authors
- Vladimir KoltchinskiiMichel TalagrandWei‐Kuo ChenSayan MukherjeeM. AriolaAlexander RakhlinP. DoratoChaouki T. Abdallah
- Topics
- Theoretical and Computational Physics (23 papers)Stochastic processes and statistical mechanics (16 papers)Markov Chains and Monte Carlo Methods (11 papers)
- Partner nations
- United StatesCanadaItaly
In The Last Decade
Dmitry Panchenko
41 papers receiving 776 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 331
- Condensed Matter Physics 265
- Statistics and Probability 264
- Mathematical Physics 165
- Computational Theory and Mathematics 161
Countries citing papers authored by Dmitry Panchenko
This map shows the geographic impact of Dmitry Panchenko'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 Dmitry Panchenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitry Panchenko more than expected).
Fields of papers citing papers by Dmitry Panchenko
This network shows the impact of papers produced by Dmitry Panchenko. 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 Dmitry Panchenko. The network helps show where Dmitry Panchenko may publish in the future.
Co-authorship network of co-authors of Dmitry Panchenko
This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry Panchenko. A scholar is included among the top collaborators of Dmitry Panchenko 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 Dmitry Panchenko. Dmitry Panchenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 8 | |
| 5 | 10 | |
| 6 | 10 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 22 | |
| 10 | 17 | |
| 11 | 4 | |
| 12 | Local Bounds based on Log-Concavity Property of the Error Probability in Wireless Communication Systems | 2 |
| 13 | 6 | |
| 14 | 25 | |
| 15 | 18.05 Introduction to Probability and Statistics, Spring 2005 | 3 |
| 16 | 28 | |
| 17 | 24 | |
| 18 | Free energy in the Sherrington-Kirkpatrick model with the constraint on the average of spins | 1 |
| 19 | 54 | |
| 20 | 1 |
About Dmitry Panchenko
Dmitry Panchenko is a scholar working on Statistics and Probability, Condensed Matter Physics and Mathematical Physics, having authored 42 papers that have together received 825 indexed citations. Recurring topics across this work include Theoretical and Computational Physics (23 papers), Stochastic processes and statistical mechanics (16 papers) and Markov Chains and Monte Carlo Methods (11 papers). The work is most often cited by research in Statistics and Probability (264 citations), Condensed Matter Physics (265 citations) and Mathematical Physics (165 citations). Dmitry Panchenko has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Vladimir Koltchinskii, Michel Talagrand, Wei‐Kuo Chen, Sayan Mukherjee, M. Ariola, Alexander Rakhlin, P. Dorato, Chaouki T. Abdallah, David Gamarnik and Jean Barbier. Their work appears in journals such as Nature, IEEE Transactions on Automatic Control and The Annals of Statistics.
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.