A. S. Kalashnikov
- Applied Mathematics top 1%
- Computational Theory and Mathematics top 1%
- Mathematical Physics top 5%
- Numerical Analysis top 2%
- Control and Systems Engineering top 10%
- Co-authors
- O A OleĭnikАрлен Михайлович ИльинВ А КондратьевYu. IlyashenkoM. I. VishikS. N. KruzhkovE. M. LandisVladimir I. Arnold
- Topics
- Advanced Mathematical Modeling in Engineering (18 papers)Differential Equations and Boundary Problems (12 papers)Differential Equations and Numerical Methods (11 papers)
- Journals
- Russian Mathematical SurveysFunctional Analysis and Its ApplicationsJournal of Applied Mathematics and Mechanics
- Partner nations
- Russia
In The Last Decade
A. S. Kalashnikov
21 papers receiving 643 citations
Peers
Comparison fields: 5 of 52
- Applied Mathematics 591
- Computational Theory and Mathematics 504
- Mathematical Physics 312
- Numerical Analysis 236
- Control and Systems Engineering 150
Countries citing papers authored by A. S. Kalashnikov
This map shows the geographic impact of A. S. Kalashnikov'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 A. S. Kalashnikov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. S. Kalashnikov more than expected).
Fields of papers citing papers by A. S. Kalashnikov
This network shows the impact of papers produced by A. S. Kalashnikov. 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 A. S. Kalashnikov. The network helps show where A. S. Kalashnikov may publish in the future.
Co-authorship network of co-authors of A. S. Kalashnikov
This figure shows the co-authorship network connecting the top 25 collaborators of A. S. Kalashnikov. A scholar is included among the top collaborators of A. S. Kalashnikov 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 A. S. Kalashnikov. A. S. Kalashnikov 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 | 15 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | Some problems of the non-linear theory of heat conduction with data containing a small parameter in the exponents | 3 |
| 6 | 6 | |
| 7 | On the diffusion of impurities with long-range action | 0 |
| 8 | 5 | |
| 9 | 43 | |
| 10 | 1 | |
| 11 | 15 | |
| 12 | 9 | |
| 13 | 5 | |
| 14 | 0 | |
| 15 | 0 | |
| 16 | 1 | |
| 17 | 3 | |
| 18 | 11 | |
| 19 | 4 | |
| 20 | 238 |
About A. S. Kalashnikov
A. S. Kalashnikov is a scholar working on Numerical Analysis, Applied Mathematics and Computational Theory and Mathematics, having authored 27 papers that have together received 829 indexed citations. Recurring topics across this work include Advanced Mathematical Modeling in Engineering (18 papers), Differential Equations and Boundary Problems (12 papers) and Differential Equations and Numerical Methods (11 papers). The work is most often cited by research in Applied Mathematics (591 citations), Numerical Analysis (236 citations) and Mathematical Physics (312 citations). A. S. Kalashnikov has collaborated with scholars based in Russia. Frequent co-authors include O A Oleĭnik, Арлен Михайлович Ильин, В А Кондратьев, Yu. Ilyashenko, M. I. Vishik, S. N. Kruzhkov, E. M. Landis, Vladimir I. Arnold, Alexander Filippov and Mikhail Shubin. Their work appears in journals such as Russian Mathematical Surveys, Functional Analysis and Its Applications and Journal of Applied Mathematics and Mechanics.
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.