Mikhail Genkin
Impact in
- Condensed Matter Physics top 10%
- Micro and Nano Robotics
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- Neural dynamics and brain function
Papers in
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- IoT and Edge/Fog Computing 2
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- Micro and Nano Robotics 5
- Co-authors
- Igor S. Aranson (5 shared papers)Andrey Sokolov (3 shared papers)Tatiana A. Engel (3 shared papers)Oleg D. Lavrentovich (3 shared papers)Christopher Langdon (1 shared paper)J.J. McArthur (3 shared papers)Qi‐Huo Wei (2 shared papers)Taras Turiv (2 shared papers)
- Journals
- Physical Review X (1 paper)Engineering Applications of Artificial Intelligence (1 paper)Nature Machine Intelligence (1 paper)New Journal of Physics (1 paper)Nature (1 paper)
- Partner nations
- United StatesCanadaGeorgia
In The Last Decade
Mikhail Genkin
14 papers receiving 325 citations
Peers
Comparison fields: 5 of 68
- Condensed Matter Physics 166
- Cognitive Neuroscience 64
- Mechanical Engineering 104
- Electronic, Optical and Magnetic Materials 50
- Statistical and Nonlinear Physics 25
Countries citing papers authored by Mikhail Genkin
This map shows the geographic impact of Mikhail Genkin'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 Mikhail Genkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikhail Genkin more than expected).
Fields of papers citing papers by Mikhail Genkin
This network shows the impact of papers produced by Mikhail Genkin. 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 Mikhail Genkin. The network helps show where Mikhail Genkin may publish in the future.
Co-authors
The 16 scholars most cited alongside Mikhail Genkin, 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 | 2017 | 90 | |
| 2 | 2023 | 63 | |
| 3 | 2020 | 61 | |
| 4 | 2023 | 23 | |
| 5 | 2018 | 22 | |
| 6 | 2020 | 19 | |
| 7 | 2020 | 19 | |
| 8 | 2022 | 13 | |
| 9 | 2016 | 7 | |
| 10 | 2025 | 6 | |
| 11 | 2019 | 2 | |
| 12 | 2022 | 2 | |
| 13 | 2022 | 1 | |
| 14 | 2020 | 1 |
About Mikhail Genkin
Mikhail Genkin is a scholar working on Computer Networks and Communications, Condensed Matter Physics, Artificial Intelligence, Mechanical Engineering and Cellular and Molecular Neuroscience, having authored 14 papers that have together received 329 indexed citations. Recurring topics across this work include Micro and Nano Robotics (5 papers), Advanced Materials and Mechanics (2 papers), Context-Aware Activity Recognition Systems (2 papers), Memory and Neural Mechanisms (2 papers), IoT and Edge/Fog Computing (2 papers), Neurobiology and Insect Physiology Research (2 papers), Cloud Computing and Resource Management (2 papers) and Modular Robots and Swarm Intelligence (2 papers). The work is most often cited by research in Condensed Matter Physics (166 citations), Cognitive Neuroscience (64 citations), Mechanical Engineering (104 citations), Electronic, Optical and Magnetic Materials (50 citations) and Statistical and Nonlinear Physics (25 citations). Mikhail Genkin has collaborated with scholars based in United States, Canada and Georgia. Frequent co-authors include Igor S. Aranson, Andrey Sokolov, Tatiana A. Engel, Oleg D. Lavrentovich, Christopher Langdon, J.J. McArthur, Qi‐Huo Wei, Taras Turiv, Hao Yu and Chenhui Peng. Their work appears in journals such as Physical Review X, Engineering Applications of Artificial Intelligence, Nature Machine Intelligence, New Journal of Physics and Nature.
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.