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)Tatiana A. Engel (3 shared papers)Andrey Sokolov (3 shared papers)Oleg D. Lavrentovich (3 shared papers)Christopher Langdon (1 shared paper)J.J. McArthur (3 shared papers)Hao Yu (2 shared papers)Taras Turiv (2 shared papers)
- Journals
- Nature reviews. Neuroscience (1 paper)Engineering Applications of Artificial Intelligence (1 paper)Nature Physics (1 paper)Physical Review X (1 paper)Nature (1 paper)
- Partner nations
- United StatesCanadaDenmark
In The Last Decade
Mikhail Genkin
14 papers receiving 347 citations
Peers
Comparison fields: 5 of 70
- Condensed Matter Physics 171
- Cognitive Neuroscience 68
- Mechanical Engineering 105
- Electronic, Optical and Magnetic Materials 48
- Cellular and Molecular Neuroscience 37
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 18 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 | 93 | |
| 2 | 2023 | 72 | |
| 3 | 2020 | 63 | |
| 4 | 2023 | 25 | |
| 5 | 2018 | 23 | |
| 6 | 2020 | 21 | |
| 7 | 2020 | 20 | |
| 8 | 2022 | 13 | |
| 9 | 2025 | 8 | |
| 10 | 2016 | 7 | |
| 11 | 2022 | 2 | |
| 12 | 2019 | 2 | |
| 13 | 2022 | 1 | |
| 14 | 2020 | 1 | |
| 15 | 2025 | 0 |
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 15 papers that have together received 351 indexed citations. Recurring topics across this work include Micro and Nano Robotics (5 papers), Context-Aware Activity Recognition Systems (2 papers), Modular Robots and Swarm Intelligence (2 papers), IoT and Edge/Fog Computing (2 papers), Cloud Computing and Resource Management (2 papers), Neural dynamics and brain function (2 papers), Neurobiology and Insect Physiology Research (2 papers) and Memory and Neural Mechanisms (2 papers). The work is most often cited by research in Condensed Matter Physics (171 citations), Cognitive Neuroscience (68 citations), Mechanical Engineering (105 citations), Electronic, Optical and Magnetic Materials (48 citations) and Cellular and Molecular Neuroscience (37 citations). Mikhail Genkin has collaborated with scholars based in United States, Canada and Denmark. Frequent co-authors include Igor S. Aranson, Tatiana A. Engel, Andrey Sokolov, Oleg D. Lavrentovich, Christopher Langdon, J.J. McArthur, Hao Yu, Taras Turiv, Qi‐Huo Wei and Kristian Thijssen. Their work appears in journals such as Nature reviews. Neuroscience, Engineering Applications of Artificial Intelligence, Nature Physics, Physical Review X 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.