Jie Shen
- Numerical Analysis top 0.02%
- Differential Equations and Numerical Methods 49
- Numerical methods for differential equations 43
- Modeling and Simulation top 0.05%
- Computational Mechanics top 0.01%
- Advanced Numerical Methods in Computational Mathematics 102
- Computational Fluid Dynamics and Aerodynamics 48
- Fluid Dynamics and Turbulent Flows 30
- Fluid Dynamics and Thin Films 27
- Computational Theory and Mathematics top 0.05%
- Advanced Mathematical Modeling in Engineering 41
- Applied Mathematics top 0.2%
-
- Solidification and crystal growth phenomena 55
- Co-authors
- Xiaofeng YangLi-Lian WangLong‐Qing ChenJean‐Luc GuermondJie XuJiang YangP MinevJames J. Feng
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Jie Shen
280 papers receiving 17.8k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Numerical Analysis 5.7k
- Modeling and Simulation 2.8k
- Computational Mechanics 10.1k
- Computational Theory and Mathematics 3.0k
- Applied Mathematics 1.6k
Countries citing papers authored by Jie Shen
This map shows the geographic impact of Jie 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 Jie Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jie Shen more than expected).
Fields of papers citing papers by Jie Shen
This network shows the impact of papers produced by Jie 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 Jie Shen. The network helps show where Jie Shen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jie 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 | 2025 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 10 | |
| 7 | 2024 | 4 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 5 | |
| 10 | 2023 | 8 | |
| 11 | 2022 | 26 | |
| 12 | 2022 | 13 | |
| 13 | 2022 | 40 | |
| 14 | 2021 | 40 | |
| 15 | 2020 | 17 | |
| 16 | 2018 | 16 | |
| 17 | Spectral approximation of time-harmonic Maxwell equations in three-dimensional exterior domains | 2015 | 9 |
| 18 | 2012 | 59 | |
| 19 | Multiplicity of positive solutions for a Navier boundary-value problem involving the -biharmonic with critical exponent. | 2011 | 4 |
| 20 | An efficient spectral method for acoustic scattering from rough surfaces | 2007 | 37 |
About Jie Shen
Jie Shen is a scholar working on Numerical Analysis, Computational Mechanics and Modeling and Simulation, having authored 292 papers that have together received 18.9k indexed citations. Recurring topics across this work include Advanced Numerical Methods in Computational Mathematics (102 papers), Solidification and crystal growth phenomena (55 papers), Differential Equations and Numerical Methods (49 papers), Computational Fluid Dynamics and Aerodynamics (48 papers), Numerical methods for differential equations (43 papers), Advanced Mathematical Modeling in Engineering (41 papers), Fluid Dynamics and Turbulent Flows (30 papers) and Fluid Dynamics and Thin Films (27 papers). The work is most often cited by research in Numerical Analysis (5.7k citations), Modeling and Simulation (2.8k citations) and Computational Mechanics (10.1k citations). Jie Shen has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Xiaofeng Yang, Li-Lian Wang, Long‐Qing Chen, Jean‐Luc Guermond, Jie Xu, Jiang Yang, P Minev, James J. Feng, Chun Liu and Tao Tang. Their work appears in journals such as Applied Physics Letters, PLoS ONE and Journal of Applied 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.