K. Shen
Impact in
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- Statistical Mechanics and Entropy
- Advanced Thermodynamics and Statistical Mechanics
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- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle physics theoretical and experimental studies
Papers in
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- Statistical Mechanics and Entropy 7
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- Fractional Differential Equations Solutions 3
- COVID-19 epidemiological studies 2
- Co-authors
- Tamás S. Bíró (3 shared papers)Enke Wang (3 shared papers)Ben-Wei Zhang (3 shared papers)G. Bíró (1 shared paper)G. G. Barnaföldi (1 shared paper)Defu Hou (1 shared paper)Yang Liu (2 shared papers)Xusheng Liu (1 shared paper)
In The Last Decade
K. Shen
9 papers receiving 61 citations
Peers
Comparison fields: 5 of 22
- Statistical and Nonlinear Physics 46
- Nuclear and High Energy Physics 34
- Modeling and Simulation 10
- Statistics and Probability 12
- Economics and Econometrics 16
Countries citing papers authored by K. Shen
This map shows the geographic impact of K. Shen'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 K. Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. Shen more than expected).
Fields of papers citing papers by K. Shen
This network shows the impact of papers produced by K. Shen. 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 K. Shen. The network helps show where K. Shen may publish in the future.
Co-authors
The 11 scholars most cited alongside K. Shen, 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 | 2018 | 14 | |
| 2 | 2015 | 13 | |
| 3 | 2017 | 10 | |
| 4 | 2017 | 10 | |
| 5 | 2017 | 9 | |
| 6 | 2022 | 4 | |
| 7 | 2019 | 3 | |
| 8 | 2015 | 1 | |
| 9 | 2024 | 1 | |
| 10 | 2023 | 0 | |
| 11 | 2022 | 0 |
About K. Shen
K. Shen is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation, Nuclear and High Energy Physics, Statistics and Probability and Atomic and Molecular Physics, and Optics, having authored 11 papers that have together received 65 indexed citations. Recurring topics across this work include Statistical Mechanics and Entropy (7 papers), High-Energy Particle Collisions Research (5 papers), Fractional Differential Equations Solutions (3 papers), Complex Systems and Time Series Analysis (2 papers), COVID-19 epidemiological studies (2 papers), Statistical Distribution Estimation and Applications (2 papers), Quantum Chromodynamics and Particle Interactions (1 paper) and Statistical Methods and Bayesian Inference (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (46 citations), Nuclear and High Energy Physics (34 citations), Modeling and Simulation (10 citations), Statistics and Probability (12 citations) and Economics and Econometrics (16 citations). K. Shen has collaborated with scholars based in China and Hungary. Frequent co-authors include Tamás S. Bíró, Enke Wang, Ben-Wei Zhang, G. Bíró, G. G. Barnaföldi, Defu Hou, Yang Liu, Xusheng Liu, Jiaming Liao and Shiyong Chen. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Physical review. D, Journal of Physics G Nuclear and Particle Physics, Advances in High Energy Physics and Communications in Theoretical Physics.
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.