V. V. Makarov
- Cognitive Neuroscience top 5%
- Artificial Intelligence top 10%
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering
- Cellular and Molecular Neuroscience
- Co-authors
- Alexander E. HramovVladimir MaksimenkoА. А. КороновскийAlexander N. PisarchikAnnika LüttjohannGilles van LuijtelaarAnastasiya E. RunnovaNikita Frolov
- Topics
- Geotechnical and Geomechanical Engineering (17 papers)Neural dynamics and brain function (14 papers)EEG and Brain-Computer Interfaces (10 papers)
- Journals
- Physical Review LettersSHILAP Revista de lepidopterologíaPLoS ONE
In The Last Decade
V. V. Makarov
53 papers receiving 647 citations
Peers
Comparison fields: 5 of 95
- Cognitive Neuroscience 355
- Artificial Intelligence 125
- Atomic and Molecular Physics, and Optics 104
- Electrical and Electronic Engineering 80
- Cellular and Molecular Neuroscience 79
Countries citing papers authored by V. V. Makarov
This map shows the geographic impact of V. V. Makarov'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 V. V. Makarov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. V. Makarov more than expected).
Fields of papers citing papers by V. V. Makarov
This network shows the impact of papers produced by V. V. Makarov. 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 V. V. Makarov. The network helps show where V. V. Makarov may publish in the future.
Co-authorship network of co-authors of V. V. Makarov
This figure shows the co-authorship network connecting the top 25 collaborators of V. V. Makarov. A scholar is included among the top collaborators of V. V. Makarov 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 V. V. Makarov. V. V. Makarov 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 | 93 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | Chaos and hyperchaos in driven interacting quantum systems | 1 |
| 7 | 47 | |
| 8 | 41 | |
| 9 | 44 | |
| 10 | 27 | |
| 11 | 2 | |
| 12 | 3 | |
| 13 | 12 | |
| 14 | 82 | |
| 15 | 46 | |
| 16 | 1 | |
| 17 | 2 | |
| 18 | 36 | |
| 19 | 6 | |
| 20 | 1 |
About V. V. Makarov
V. V. Makarov is a scholar working on Mechanics of Materials, Cognitive Neuroscience and Statistical and Nonlinear Physics, having authored 59 papers that have together received 674 indexed citations. Recurring topics across this work include Geotechnical and Geomechanical Engineering (17 papers), Neural dynamics and brain function (14 papers) and EEG and Brain-Computer Interfaces (10 papers). The work is most often cited by research in Cognitive Neuroscience (355 citations), Statistical and Nonlinear Physics (69 citations) and Cellular and Molecular Neuroscience (79 citations). V. V. Makarov has collaborated with scholars based in Russia, Spain and Germany. Frequent co-authors include Alexander E. Hramov, Vladimir Maksimenko, А. А. Короновский, Alexander N. Pisarchik, Annika Lüttjohann, Gilles van Luijtelaar, Anastasiya E. Runnova, Nikita Frolov, Vadim Grubov and T. M. Fromhold. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and PLoS ONE.
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.