Shanwu Li

640 total citations
24 papers, 474 citations indexed

About

Shanwu Li is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Civil and Structural Engineering. According to data from OpenAlex, Shanwu Li has authored 24 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Mechanics, 9 papers in Statistical and Nonlinear Physics and 7 papers in Civil and Structural Engineering. Recurrent topics in Shanwu Li's work include Fluid Dynamics and Vibration Analysis (11 papers), Model Reduction and Neural Networks (9 papers) and Wind and Air Flow Studies (6 papers). Shanwu Li is often cited by papers focused on Fluid Dynamics and Vibration Analysis (11 papers), Model Reduction and Neural Networks (9 papers) and Wind and Air Flow Studies (6 papers). Shanwu Li collaborates with scholars based in United States, China and Denmark. Shanwu Li's co-authors include Shujin Laima, Hui Li, Yongchao Yang, Hui Li, Steven L. Brunton, J. Nathan Kutz, Eurika Kaiser, Wen‐Li Chen, Nan Xu and Charles R. Farrar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Optics Letters and Journal of Sound and Vibration.

In The Last Decade

Shanwu Li

21 papers receiving 465 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shanwu Li United States 10 227 181 135 83 79 24 474
Guido Morgenthal Germany 14 229 1.0× 315 1.7× 207 1.5× 111 1.3× 24 0.3× 44 539
Antoine Blanchard United States 13 171 0.8× 183 1.0× 65 0.5× 167 2.0× 64 0.8× 24 411
Jiřı́ Náprstek Czechia 15 239 1.1× 219 1.2× 171 1.3× 284 3.4× 91 1.2× 77 601
Cristian Guillermo Gebhardt Germany 16 263 1.2× 163 0.9× 128 0.9× 156 1.9× 25 0.3× 56 585
Luca Bonfiglio United States 12 74 0.3× 188 1.0× 73 0.5× 25 0.3× 45 0.6× 30 405
X. Q. Wang United States 13 266 1.2× 183 1.0× 113 0.8× 208 2.5× 34 0.4× 35 497
Frédéric Bourquin France 14 266 1.2× 60 0.3× 53 0.4× 81 1.0× 50 0.6× 43 467
A.S. Zymaris Greece 8 158 0.7× 144 0.8× 56 0.4× 14 0.2× 30 0.4× 10 369
Mohammad Javad Kazemzadeh‐Parsi Iran 12 195 0.9× 103 0.6× 54 0.4× 31 0.4× 30 0.4× 30 406
E.M. Papoutsis‐Kiachagias Greece 13 290 1.3× 239 1.3× 47 0.3× 17 0.2× 49 0.6× 35 582

Countries citing papers authored by Shanwu Li

Since Specialization
Citations

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

Fields of papers citing papers by Shanwu Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanwu Li

This figure shows the co-authorship network connecting the top 25 collaborators of Shanwu Li. A scholar is included among the top collaborators of Shanwu Li 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 Shanwu Li. Shanwu Li 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.
Li, Shanwu, et al.. (2025). A super-sensitivity incoherent optical method with time-delay embedding for pixel-limited dynamic displacement measurements. Mechanical Systems and Signal Processing. 230. 112546–112546.
2.
Mao, Zai‐Sha, et al.. (2025). Physics-constrained normalizing flow for identification and modeling of vortex-induced vibration in stay cables. Nonlinear Dynamics. 113(23). 32167–32186.
3.
4.
Li, Shanwu & Yongchao Yang. (2024). Data-driven modeling of bifurcation systems by learning the bifurcation parameter generalization. Nonlinear Dynamics. 113(2). 1163–1174. 2 indexed citations
5.
Li, Shanwu, et al.. (2024). Machine learning for bridge wind engineering. SHILAP Revista de lepidopterología. 1(1). 100002–100002. 28 indexed citations
6.
Du, Tao, et al.. (2024). Deciphering the controlling factors for phase transitions in zeolitic imidazolate frameworks. National Science Review. 11(4). nwae023–nwae023. 16 indexed citations
7.
Li, Shanwu, et al.. (2023). A study on data-driven identification and representation of nonlinear dynamical systems with a physics-integrated deep learning approach: Koopman operators and nonlinear normal modes. Communications in Nonlinear Science and Numerical Simulation. 123. 107278–107278. 3 indexed citations
8.
Li, Shanwu & Yongchao Yang. (2023). Efficient Data-Driven Modeling of Nonlinear Dynamical Systems via Metalearning. Journal of Engineering Mechanics. 149(3). 1 indexed citations
9.
Li, Shanwu & Yongchao Yang. (2023). A deep generative framework for data-driven surrogate modeling and visualization of parameterized nonlinear dynamical systems. Nonlinear Dynamics. 111(11). 10287–10307. 5 indexed citations
10.
Li, Shanwu, et al.. (2023). Data-Driven Modeling of Parameterized Nonlinear Dynamical Systems with a Dynamics-Embedded Conditional Generative Adversarial Network. Journal of Engineering Mechanics. 149(11). 1 indexed citations
11.
Li, Shanwu, Charles R. Farrar, & Yongchao Yang. (2023). Efficient regional seismic risk assessment via deep generative learning of surrogate models. Earthquake Engineering & Structural Dynamics. 52(11). 3435–3454. 8 indexed citations
12.
Li, Shanwu, et al.. (2023). On the Fundamental Sensitivity Limit of Incoherent Optical Methods for Full-Field Displacement Measurements. IEEE Transactions on Instrumentation and Measurement. 72. 1–4. 4 indexed citations
13.
Li, Shanwu & Yongchao Yang. (2022). Super-sensitivity incoherent optical methods for full-field displacement measurements. Optics Letters. 47(21). 5453–5453. 5 indexed citations
14.
Li, Shanwu, et al.. (2021). Data‐driven modeling of bridge buffeting in the time domain using long short‐term memory network based on structural health monitoring. Structural Control and Health Monitoring. 28(8). 47 indexed citations
15.
Li, Shanwu & Yongchao Yang. (2021). A recurrent neural network framework with an adaptive training strategy for long-time predictive modeling of nonlinear dynamical systems. Journal of Sound and Vibration. 506. 116167–116167. 19 indexed citations
16.
Li, Shanwu & Yongchao Yang. (2021). Data-driven identification of nonlinear normal modes via physics-integrated deep learning. Nonlinear Dynamics. 106(4). 3231–3246. 23 indexed citations
17.
Li, Shanwu & Yongchao Yang. (2021). Hierarchical deep learning for data-driven identification of reduced-order models of nonlinear dynamical systems. Nonlinear Dynamics. 105(4). 3409–3422. 11 indexed citations
18.
Li, Shanwu, Eurika Kaiser, Shujin Laima, et al.. (2019). Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems. Physical review. E. 100(2). 22220–22220. 51 indexed citations
19.
Li, Shanwu, Shujin Laima, & Hui Li. (2017). Data-driven modeling of vortex-induced vibration of a long-span suspension bridge using decision tree learning and support vector regression. Journal of Wind Engineering and Industrial Aerodynamics. 172. 196–211. 126 indexed citations
20.
Li, Shanwu. (2011). A Judging Method for the Threatening Grade of Emitter Based on MADM. 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Guido Morgenthal Breakdown of academic impact, for papers by Antoine Blanchard Breakdown of academic impact, for papers by Jiřı́ Náprstek Breakdown of academic impact, for papers by Cristian Guillermo Gebhardt Breakdown of academic impact, for papers by Luca Bonfiglio Breakdown of academic impact, for papers by X. Q. Wang Breakdown of academic impact, for papers by Frédéric Bourquin Breakdown of academic impact, for papers by A.S. Zymaris Breakdown of academic impact, for papers by Mohammad Javad Kazemzadeh‐Parsi Breakdown of academic impact, for papers by E.M. Papoutsis‐Kiachagias
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2026