Shili Chen

2.3k total citations · 1 hit paper
54 papers, 1.3k citations indexed

About

Shili Chen is a scholar working on Mechanical Engineering, Mechanics of Materials and Biomedical Engineering. According to data from OpenAlex, Shili Chen has authored 54 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Mechanical Engineering, 17 papers in Mechanics of Materials and 9 papers in Biomedical Engineering. Recurrent topics in Shili Chen's work include Ultrasonics and Acoustic Wave Propagation (14 papers), Non-Destructive Testing Techniques (14 papers) and Magnetic Properties and Applications (4 papers). Shili Chen is often cited by papers focused on Ultrasonics and Acoustic Wave Propagation (14 papers), Non-Destructive Testing Techniques (14 papers) and Magnetic Properties and Applications (4 papers). Shili Chen collaborates with scholars based in China, United States and Singapore. Shili Chen's co-authors include Alan Saghatelian, Tejia Zhang, Barbara B. Kahn, Ismail Syed, Edwin A. Homan, Ulf Smith, Ann Hammarstedt, Jennifer Lee, Rajesh T. Patel and Timothy E. McGraw and has published in prestigious journals such as Cell, Cell Metabolism and Nature Protocols.

In The Last Decade

Shili Chen

52 papers receiving 1.3k citations

Hit Papers

Discovery of a Class of Endogenous Mammalian Lipids with ... 2014 2026 2018 2022 2014 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shili Chen China 13 498 251 175 160 149 54 1.3k
Cheng‐Hsien Chen Taiwan 27 679 1.4× 196 0.8× 114 0.7× 62 0.4× 115 0.8× 98 1.9k
Peter S. Stewart United Kingdom 22 509 1.0× 184 0.7× 126 0.7× 68 0.4× 187 1.3× 68 1.9k
Partha Chakrabarti India 28 915 1.8× 652 2.6× 47 0.3× 292 1.8× 394 2.6× 112 2.6k
Minoru HAMADA Japan 21 558 1.1× 153 0.6× 135 0.8× 295 1.8× 123 0.8× 191 1.7k
Wenrui Liu China 28 597 1.2× 120 0.5× 362 2.1× 47 0.3× 71 0.5× 131 3.2k
Xi Qiu China 23 344 0.7× 139 0.6× 307 1.8× 30 0.2× 124 0.8× 99 1.8k
Toshihiro Takahashi Japan 23 650 1.3× 237 0.9× 42 0.2× 127 0.8× 115 0.8× 168 2.0k
Xianghui Chen China 24 869 1.7× 78 0.3× 225 1.3× 47 0.3× 139 0.9× 107 2.3k
Liang Yu China 30 554 1.1× 95 0.4× 191 1.1× 82 0.5× 56 0.4× 120 3.0k
Yukio Fujimoto Japan 20 434 0.9× 96 0.4× 87 0.5× 36 0.2× 51 0.3× 135 1.4k

Countries citing papers authored by Shili Chen

Since Specialization
Citations

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

Fields of papers citing papers by Shili Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shili Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Shili Chen. A scholar is included among the top collaborators of Shili 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 Shili Chen. Shili 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.
Yu, Jiaping, Yutong Chen, Juan Zhuang, et al.. (2025). Single-cell transcriptome analysis identifies MIF as a novel tumor-associated neutrophil marker for pancreatic ductal adenocarcinoma. npj Precision Oncology. 9(1). 293–293. 1 indexed citations
2.
Li, Jian, et al.. (2024). Quantitative guided wave imaging with shear horizontal waves and deep convolutional descent full waveform inversion. NDT & E International. 145. 103141–103141. 7 indexed citations
3.
Li, Jian, et al.. (2024). Deep Learning With Physics-Embedded Neural Network for Full Waveform Ultrasonic Brain Imaging. IEEE Transactions on Medical Imaging. 43(6). 2332–2346. 12 indexed citations
4.
Li, Jian, et al.. (2024). Finite difference-embedded UNet for solving transcranial ultrasound frequency-domain wavefield. The Journal of the Acoustical Society of America. 155(3). 2257–2269. 7 indexed citations
5.
Wang, Taoyang, et al.. (2024). Comparative analysis of SAR ship detection methods based on deep learning. IET conference proceedings.. 2023(47). 3918–3925. 2 indexed citations
6.
Li, Jian, et al.. (2024). Unveiling the potential of ultrasound in brain imaging: Innovations, challenges, and prospects. Ultrasonics. 145. 107465–107465. 6 indexed citations
7.
Lyu, Yan, et al.. (2024). Advances in acoustic techniques for evaluating defects and properties in lithium-ion batteries: A review. Ultrasonics. 142. 107400–107400. 4 indexed citations
8.
Yang, Jiahua, Xuechuan Li, Shili Chen, et al.. (2024). GPRC5A promotes gallbladder cancer metastasis by upregulating TNS4 via the JAK2–STAT3 pathway. Cancer Letters. 598. 217067–217067. 5 indexed citations
9.
Zeng, Zhoumo, et al.. (2023). Imaging and characterization of cement annulus and bonding interfaces in cased wells with fully connected neural network. Geophysics. 88(6). D357–D369. 6 indexed citations
10.
Lv, Lingling, et al.. (2023). Ultrasonic guided wave imaging of pipelines based on physics embedded inversion neural network. Measurement Science and Technology. 34(11). 115401–115401. 7 indexed citations
11.
Li, Jiayue, et al.. (2023). Research Hotspots and Trends of Bone Xenograft in Clinical Procedures: A Bibliometric and Visual Analysis of the Past Decade. Bioengineering. 10(8). 929–929. 2 indexed citations
12.
Zeng, Zhoumo, et al.. (2023). The effect of error coefficient matrices and correlation criteria on dic computation errors. Optics and Lasers in Engineering. 174. 107954–107954. 3 indexed citations
13.
Wang, Xiaocen, et al.. (2023). Joint learning of sparse and limited-view guided waves signals for feature reconstruction and imaging. Ultrasonics. 137. 107200–107200. 7 indexed citations
14.
Yu, Xiao, Wei Lu, Shuoyu Xu, et al.. (2020). Computer‐aided assessment of the chemokine receptors CXCR3, CXCR4 and CXCR7 expression in gallbladder carcinoma. Journal of Cellular and Molecular Medicine. 24(13). 7670–7674. 3 indexed citations
15.
Wei, Wei, Adam G. Schwaid, Xueqian Wang, et al.. (2016). Ligand Activation of ERRα by Cholesterol Mediates Statin and Bisphosphonate Effects. Cell Metabolism. 23(3). 479–491. 123 indexed citations
16.
Zhang, Tejia, Shili Chen, Ismail Syed, et al.. (2016). A LC-MS–based workflow for measurement of branched fatty acid esters of hydroxy fatty acids. Nature Protocols. 11(4). 747–763. 67 indexed citations
17.
Chen, Shili, et al.. (2014). CFD and Experimental Investigations of Drag Force onSpherical Leak Detector in Pipe Flows at High ReynoldsNumber. Computer Modeling in Engineering & Sciences. 101(1). 59–80. 1 indexed citations
18.
Yore, Mark M., Ismail Syed, Pedro M. Moraes‐Vieira, et al.. (2014). Discovery of a Class of Endogenous Mammalian Lipids with Anti-Diabetic and Anti-inflammatory Effects. Cell. 159(2). 318–332. 648 indexed citations breakdown →
19.
Chen, Shili, et al.. (2013). Simulation Study on the Acoustic Field from LinearPhased Array Ultrasonic Transducer for Engine CylinderTesting. Computer Modeling in Engineering & Sciences. 90(6). 487–500. 3 indexed citations
20.
Chen, Shili. (2013). Sound-field of Discrete Point Sources Simulation on Deflecting and Focusing of Near-field of Ultrasonic Phased Array. Jisuanji fangzhen. 2 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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