Yong Chen

8.4k total citations · 1 hit paper
279 papers, 6.9k citations indexed

About

Yong Chen is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Yong Chen has authored 279 papers receiving a total of 6.9k indexed citations (citations by other indexed papers that have themselves been cited), including 264 papers in Statistical and Nonlinear Physics, 65 papers in Modeling and Simulation and 64 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Yong Chen's work include Nonlinear Waves and Solitons (232 papers), Nonlinear Photonic Systems (195 papers) and Fractional Differential Equations Solutions (65 papers). Yong Chen is often cited by papers focused on Nonlinear Waves and Solitons (232 papers), Nonlinear Photonic Systems (195 papers) and Fractional Differential Equations Solutions (65 papers). Yong Chen collaborates with scholars based in China, United States and Japan. Yong Chen's co-authors include Biao Li, Xiaoen Zhang, Hongqing Zhang, Xiaorui Hu, Lili Huang, Juncai Pu, Zhenya Yan, Bo Yang, Sen‐Yue Lou and Yuqi Li and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Scientific Reports and Journal of Computational Physics.

In The Last Decade

Yong Chen

271 papers receiving 6.5k citations

Hit Papers

A two-stage physics-informed neural network method based ... 2022 2026 2023 2024 2022 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yong Chen China 45 6.5k 1.8k 1.7k 1.3k 783 279 6.9k
Zhenya Yan China 38 4.4k 0.7× 1.8k 1.0× 910 0.5× 501 0.4× 544 0.7× 226 4.9k
Engui Fan China 42 8.3k 1.3× 1.5k 0.9× 2.7k 1.5× 2.0k 1.6× 1.2k 1.5× 222 8.6k
Peter A. Clarkson United Kingdom 35 8.1k 1.3× 1.9k 1.1× 1.8k 1.0× 2.1k 1.7× 1.3k 1.6× 105 8.9k
Nail H. Ibragimov Sweden 28 3.3k 0.5× 1.1k 0.6× 1.0k 0.6× 691 0.5× 634 0.8× 127 4.8k
Junkichi Satsuma Japan 38 6.3k 1.0× 1.7k 1.0× 988 0.6× 2.0k 1.6× 1.1k 1.5× 134 7.0k
George W. Bluman Canada 31 5.8k 0.9× 742 0.4× 1.5k 0.9× 1.3k 1.0× 850 1.1× 73 7.1k
Hadi Rezazadeh Iran 57 9.3k 1.4× 2.4k 1.3× 5.7k 3.2× 783 0.6× 762 1.0× 336 10.6k
Sachin Kumar India 42 4.6k 0.7× 769 0.4× 2.0k 1.2× 773 0.6× 540 0.7× 171 5.1k
Jalil Manafian Iran 41 5.4k 0.8× 1.0k 0.6× 3.5k 2.0× 618 0.5× 515 0.7× 205 6.3k
Ahmet Bekir Türkiye 48 7.5k 1.1× 1.2k 0.7× 4.8k 2.8× 860 0.7× 620 0.8× 342 8.0k

Countries citing papers authored by Yong Chen

Since Specialization
Citations

This map shows the geographic impact of Yong Chen'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 Yong Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yong Chen more than expected).

Fields of papers citing papers by Yong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yong Chen. 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 Yong Chen. The network helps show where Yong Chen may publish in the future.

Co-authorship network of co-authors of Yong Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Yong Chen. A scholar is included among the top collaborators of Yong Chen 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 Yong Chen. Yong Chen 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.
Chen, Yong, et al.. (2025). PE-RWP: A deep learning framework for polynomial feature extraction of rogue wave patterns and peregrine waves localization. Journal of Computational Physics. 539. 114243–114243. 2 indexed citations
2.
Zhou, Huijuan & Yong Chen. (2025). Gradient-enhanced PINN with residual unit for studying forward-inverse problems of variable coefficient equations. Physica D Nonlinear Phenomena. 481. 134764–134764. 2 indexed citations
3.
Peng, Wei‐Qi & Yong Chen. (2025). Long-time asymptotics for a fourth-order dispersive nonlinear Schrödinger equation with nonzero boundary conditions. Journal of Mathematical Analysis and Applications. 553(2). 129879–129879.
4.
Pu, Juncai & Yong Chen. (2024). Lax pairs informed neural networks solving integrable systems. Journal of Computational Physics. 510. 113090–113090. 23 indexed citations
5.
Chen, Yong, et al.. (2024). Pseudo grid-based physics-informed convolutional-recurrent network solving the integrable nonlinear lattice equations. Physica D Nonlinear Phenomena. 468. 134304–134304. 3 indexed citations
6.
Zhang, Wenxin & Yong Chen. (2024). Riemann-hilbert problem and physics-informed neural networks method for the nonlocal Sasa-Satsuma equation. Nonlinear Dynamics. 113(9). 10211–10227.
7.
Peng, Wei‐Qi & Yong Chen. (2024). Long-time asymptotics for the integrable nonlocal Lakshmanan–Porsezian–Daniel equation with decaying initial value data. Applied Mathematics Letters. 152. 109030–109030. 4 indexed citations
8.
Chen, Yong, Libin Li, & Ying Zheng. (2024). Irreducible Z+-modules over a class of domains. Communications in Algebra. 53(1). 11–17.
9.
Pu, Juncai & Yong Chen. (2023). Double and triple-pole solutions for the third-order flow equation of the Kaup-Newell system with zero/nonzero boundary conditions. Journal of Mathematical Physics. 64(10). 3 indexed citations
10.
Peng, Wei‐Qi & Yong Chen. (2022). N-double poles solutions for nonlocal Hirota equation with nonzero boundary conditions using Riemann–Hilbert method and PINN algorithm. Physica D Nonlinear Phenomena. 435. 133274–133274. 60 indexed citations
11.
Li, Jun & Yong Chen. (2020). Solving second-order nonlinear evolution partial differential equations using deep learning*. Communications in Theoretical Physics. 72(10). 105005–105005. 62 indexed citations
12.
Li, Jun & Yong Chen. (2020). A deep learning method for solving third-order nonlinear evolution equations. Communications in Theoretical Physics. 72(11). 115003–115003. 74 indexed citations
13.
Li, Jun & Yong Chen. (2020). A physics-constrained deep residual network for solving the sine-Gordon equation. Communications in Theoretical Physics. 73(1). 15001–15001. 28 indexed citations
14.
Deng, Xiaolong, Hao Ding, Yong Chen, Chen Cai, & Tiejun Lv. (2020). Novel Node Centrality-Based Efficient Empirical Robustness Assessment for Directed Network. Complexity. 2020. 1–14. 2 indexed citations
15.
Yang, Bo & Yong Chen. (2018). Reductions of Darboux transformations for the PT-symmetric nonlocal Davey–Stewartson equations. Applied Mathematics Letters. 82. 43–49. 31 indexed citations
16.
Chen, Junchao, Bao‐Feng Feng, & Yong Chen. (2017). Bilinear Bäcklund transformation, Lax pair and multi-soliton solution for a vector Ramani equation. Modern Physics Letters B. 31(12). 1750133–1750133. 6 indexed citations
17.
Huang, Lili & Yong Chen. (2016). Nonlocal symmetry and similarity reductions for the Drinfeld–Sokolov–Satsuma–Hirota system. Applied Mathematics Letters. 64. 177–184. 43 indexed citations
18.
Qian, Miao, Xiangpeng Xin, & Yong Chen. (2013). Nonlocal symmetries and explicit solutions of the AKNS system. Applied Mathematics Letters. 28. 7–13. 16 indexed citations
19.
Bing-nan, Sun, et al.. (2006). METHOD OF BRIDGE HEALTH MONITORING BASED ON WAVELET ANALYSIS. Engineering Mechanics. 23(12). 129–135. 12 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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