Jie Shen

25.4k total citations · 10 hit papers
292 papers, 18.9k citations indexed

About

Jie Shen is a scholar working on Computational Mechanics, Numerical Analysis and Materials Chemistry. According to data from OpenAlex, Jie Shen has authored 292 papers receiving a total of 18.9k indexed citations (citations by other indexed papers that have themselves been cited), including 150 papers in Computational Mechanics, 81 papers in Numerical Analysis and 66 papers in Materials Chemistry. Recurrent topics in Jie Shen's work include Advanced Numerical Methods in Computational Mathematics (102 papers), Solidification and crystal growth phenomena (55 papers) and Differential Equations and Numerical Methods (49 papers). Jie Shen is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (102 papers), Solidification and crystal growth phenomena (55 papers) and Differential Equations and Numerical Methods (49 papers). Jie Shen collaborates with scholars based in United States, China and Singapore. Jie Shen's 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 and has published in prestigious journals such as Applied Physics Letters, PLoS ONE and Journal of Applied Physics.

In The Last Decade

Jie Shen

280 papers receiving 17.8k citations

Hit Papers

An overview of projection methods for incompressible f... 1994 2026 2004 2015 2006 2011 1998 2004 2011 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. An overview of projection methods for incompressible flows
    2006 970 citations Jie Shen et al. Computer Methods in Applied Mechanics and Engineering profile →
  2. Spectral Methods
    2011 929 citations Jie Shen et al. profile →
  3. Applications of semi-implicit Fourier-spectral method to phase field equations
    1998 910 citations Long‐Qing Chen, Jie Shen profile →
  4. A diffuse-interface method for simulating two-phase flows of complex fluids
    2004 833 citations Jie Shen et al. profile →
  5. Spectral Methods: Algorithms, Analysis and Applications
    2011 813 citations Jie Shen et al. profile →
  6. The scalar auxiliary variable (SAV) approach for gradient flows
    2017 690 citations Jie Shen et al. Journal of Computational Physics profile →
  7. Numerical approximations of Allen-Cahn and Cahn-Hilliard equations
    2010 676 citations Jie Shen et al. profile →
  8. Efficient Spectral-Galerkin Method I. Direct Solvers of Second- and Fourth-Order Equations Using Legendre Polynomials
    1994 492 citations Jie Shen SIAM Journal on Scientific Computing profile →
  9. A phase field model for the mixture of two incompressible fluids and its approximation by a Fourier-spectral method
    2003 471 citations Chun Liu, Jie Shen profile →
  10. A New Class of Efficient and Robust Energy Stable Schemes for Gradient Flows
    2019 449 citations Jie Shen et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jie Shen United States 65 10.1k 6.4k 5.7k 3.0k 2.8k 292 18.9k
Qiang Du United States 58 4.9k 0.5× 2.4k 0.4× 2.2k 0.4× 2.2k 0.7× 1.1k 0.4× 351 13.3k
Tao Tang China 46 3.5k 0.4× 1.4k 0.2× 3.5k 0.6× 1.5k 0.5× 2.2k 0.8× 237 8.0k
M. Yousuff Hussaini United States 49 9.4k 0.9× 870 0.1× 1.9k 0.3× 1.1k 0.4× 973 0.3× 289 15.9k
Roger Témam United States 62 9.9k 1.0× 1.2k 0.2× 2.7k 0.5× 8.8k 2.9× 1.1k 0.4× 360 25.6k
Max Gunzburger United States 65 7.9k 0.8× 629 0.1× 1.8k 0.3× 3.4k 1.1× 719 0.3× 333 14.9k
Ernst Hairer Switzerland 42 6.5k 0.6× 499 0.1× 10.3k 1.8× 4.2k 1.4× 1.1k 0.4× 119 17.1k
Claudio Canuto Italy 28 5.3k 0.5× 305 0.0× 2.8k 0.5× 1.4k 0.5× 1.7k 0.6× 113 10.8k
L. F. Shampine United States 45 3.1k 0.3× 602 0.1× 3.8k 0.7× 1.8k 0.6× 709 0.2× 187 12.5k
Bernardo Cockburn United States 59 19.9k 2.0× 361 0.1× 6.0k 1.1× 3.8k 1.2× 483 0.2× 203 22.2k
C. Shu Singapore 70 13.4k 1.3× 2.7k 0.4× 797 0.1× 244 0.1× 561 0.2× 529 22.1k

Countries citing papers authored by Jie Shen

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Jie Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Jie Shen. A scholar is included among the top collaborators of Jie Shen 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 Jie Shen. Jie Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shen, Jie, et al.. (2025). Stability and error analysis of linear IMEX schemes for sixth-order Cahn–Hilliard-type equations. Communications in Nonlinear Science and Numerical Simulation. 145. 108724–108724. 1 indexed citations
2.
Shen, Jie, et al.. (2024). A new flow dynamic approach for Wasserstein gradient flows. Journal of Computational Physics. 524. 113696–113696.
3.
Ma, Ziqi, Zhiping Mao, & Jie Shen. (2024). Efficient and stable SAV-based methods for gradient flows arising from deep learning. Journal of Computational Physics. 505. 112911–112911. 1 indexed citations
4.
Li, Buyang, et al.. (2024). Efficient energy stable schemes for incompressible flows with variable density. Journal of Computational Physics. 517. 113365–113365. 4 indexed citations
5.
Yuan, Chaochun, Youguo He, Jie Shen, et al.. (2024). Neural network energy management strategy for plug-in hybrid electric combine harvesters based on quasi-periodic samples. Engineering Applications of Artificial Intelligence. 136. 109051–109051. 5 indexed citations
6.
Liu, Chen, Béatrice Rivière, Jie Shen, & Xiangxiong Zhang. (2024). A Simple and Efficient Convex Optimization Based Bound-Preserving High Order Accurate Limiter for Cahn–Hilliard–Navier–Stokes System. SIAM Journal on Scientific Computing. 46(3). A1923–A1948. 10 indexed citations
7.
Shen, Jie, et al.. (2024). On a New Class of BDF and IMEX Schemes for Parabolic Type Equations. SIAM Journal on Numerical Analysis. 62(4). 1609–1637. 4 indexed citations
8.
Shen, Jie, et al.. (2023). Bound/positivity preserving SAV schemes for the Patlak-Keller-Segel-Navier-Stokes system. Journal of Computational Physics. 480. 112034–112034. 5 indexed citations
9.
Zhang, Jiahao, et al.. (2023). Energy-dissipative evolutionary deep operator neural networks. Journal of Computational Physics. 498. 112638–112638. 5 indexed citations
10.
Sun, Jiebao, et al.. (2023). A Ginzburg-Landau-$${H}^{-1}$$ Model and Its SAV Algorithm for Image Inpainting. Journal of Scientific Computing. 96(2). 8 indexed citations
11.
Wu, Ke, et al.. (2022). A new class of higher-order decoupled schemes for the incompressible Navier-Stokes equations and applications to rotating dynamics. Journal of Computational Physics. 458. 111097–111097. 26 indexed citations
12.
Shen, Jie, et al.. (2022). Bound/positivity preserving and unconditionally stable schemes for a class of fourth order nonlinear equations. Journal of Computational Physics. 460. 111177–111177. 13 indexed citations
13.
Shen, Jie, et al.. (2022). A new class of implicit–explicit BDFk SAV schemes for general dissipative systems and their error analysis. Computer Methods in Applied Mechanics and Engineering. 392. 114718–114718. 40 indexed citations
14.
Antoine, Xavier, Jie Shen, & Qinglin Tang. (2021). Scalar Auxiliary Variable/Lagrange multiplier based pseudospectral schemes for the dynamics of nonlinear Schrödinger/Gross-Pitaevskii equations. Journal of Computational Physics. 437. 110328–110328. 40 indexed citations
15.
Zhou, Jiajun, Jie Shen, Shanqing Yu, Guanrong Chen, & Qi Xuan. (2020). M-Evolve: Structural-Mapping-Based Data Augmentation for Graph Classification. IEEE Transactions on Network Science and Engineering. 8(1). 190–200. 17 indexed citations
16.
Yang, Qingcheng, et al.. (2018). A thermodynamically consistent phase‐field model for viscous sintering. Journal of the American Ceramic Society. 102(2). 674–685. 16 indexed citations
17.
Shen, Jie, et al.. (2015). Spectral approximation of time-harmonic Maxwell equations in three-dimensional exterior domains. 12(2). 366–383. 9 indexed citations
18.
Shen, Jie, et al.. (2012). An Efficient, Energy Stable Scheme for the Cahn-Hilliard-Brinkman System. Communications in Computational Physics. 13(4). 929–957. 59 indexed citations
19.
Shen, Jie & Jihui Zhang. (2011). Multiplicity of positive solutions for a Navier boundary-value problem involving the -biharmonic with critical exponent.. 2011. 4 indexed citations
20.
Xiu, Dongbin & Jie Shen. (2007). An efficient spectral method for acoustic scattering from rough surfaces. Communications in Computational Physics. 2(1). 54–72. 37 indexed citations

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.

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