Ye Sang

2.0k total citations
15 papers, 379 citations indexed

About

Ye Sang is a scholar working on Mechanics of Materials, Materials Chemistry and Mechanical Engineering. According to data from OpenAlex, Ye Sang has authored 15 papers receiving a total of 379 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Mechanics of Materials, 6 papers in Materials Chemistry and 3 papers in Mechanical Engineering. Recurrent topics in Ye Sang's work include Machine Learning in Materials Science (3 papers), Composite Material Mechanics (3 papers) and Metallurgy and Material Forming (3 papers). Ye Sang is often cited by papers focused on Machine Learning in Materials Science (3 papers), Composite Material Mechanics (3 papers) and Metallurgy and Material Forming (3 papers). Ye Sang collaborates with scholars based in China. Ye Sang's co-authors include Xi‐Qiao Feng, Bo Li, Hongping Zhao, Qunyang Li, Guang‐Kui Xu, Shao‐Zhen Lin, Min Li, Song Gao, Qihan Li and Yanli Sun and has published in prestigious journals such as Applied Physics Letters, Biophysical Journal and Journal of Materials Science.

In The Last Decade

Ye Sang

12 papers receiving 367 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ye Sang China	8	166	143	122	73	59	15	379
Valerio Varano Italy	16	148 0.9×	307 2.1×	149 1.2×	165 2.3×	18 0.3×	54	689
Michele De Angelo Italy	9	76 0.5×	181 1.3×	154 1.3×	60 0.8×	8 0.1×	13	324
Eial Teomy Israel	5	268 1.6×	28 0.2×	43 0.4×	140 1.9×	22 0.4×	7	375
Ajeet Kumar India	14	242 1.5×	116 0.8×	104 0.9×	197 2.7×	10 0.2×	45	541
Philipp Junker Germany	16	91 0.5×	332 2.3×	186 1.5×	98 1.3×	8 0.1×	90	655
Thang X. Duong Germany	9	157 0.9×	274 1.9×	87 0.7×	81 1.1×	28 0.5×	19	537
Alessandro Ciallella Italy	14	98 0.6×	230 1.6×	206 1.7×	68 0.9×	21 0.4×	25	445
Federico Bosi United Kingdom	13	161 1.0×	117 0.8×	30 0.2×	140 1.9×	10 0.2×	27	364
Benjamin Smaniotto France	10	120 0.7×	156 1.1×	81 0.7×	88 1.2×	9 0.2×	29	427
Berkin Dortdivanlioglu United States	12	119 0.7×	82 0.6×	32 0.3×	108 1.5×	44 0.7×	22	303

Countries citing papers authored by Ye Sang

Since Specialization

Citations

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

Fields of papers citing papers by Ye Sang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ye Sang

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

All Works

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15 of 15 papers shown

Ye, Zheng, Zhuang Li, Jianfeng Zhang, et al.. (2025). Prognostic impact of tace combined with sorafenib or lenvatinib followed by regorafenib in recurrent hepatocellular carcinoma after liver transplantation: a retrospective study. BMC Cancer. 25(1). 1049–1049.

Zhang, Jing, Chengzhi Zhang, Cuiyuan Huang, et al.. (2025). Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above. BMC Geriatrics. 25(1). 458–458.

Gao, Song, et al.. (2024). Research on the thermal forming limit diagram (TFLD) with the M-K model for Ti-6Al-4V alloy. The International Journal of Advanced Manufacturing Technology. 131(7-8). 3713–3728.

Chen, Dongxu, et al.. (2023). A novel broadband windmill‐shaped metasurface antenna with stable radiation patterns. IET Microwaves Antennas & Propagation. 17(12). 955–962. 1 indexed citations

Zhang, Kaixuan, Wei Fang, Ye Sang, et al.. (2023). Drop collision analysis by using many-body dissipative particle dynamics and machine learning. Applied Physics Letters. 123(20). 3 indexed citations

Xu, Bowen, Ye Sang, Min Li, Hongping Zhao, & Xi‐Qiao Feng. (2022). Deep learning method for predicting the strengths of microcracked brittle materials. Engineering Fracture Mechanics. 271. 108600–108600. 26 indexed citations

Gao, Song, et al.. (2022). Anisotropic behavior and mechanical properties of Ti-6Al-4V alloy in high temperature deformation. Journal of Materials Science. 57(1). 651–670. 19 indexed citations

Sang, Ye, Min Li, Kaixuan Zhang, Hongping Zhao, & Xi‐Qiao Feng. (2022). Extracting the properties of constituent phases from the overall response of composites: A deep neural network method. Composite Structures. 293. 115707–115707. 7 indexed citations

Xu, Yiming, Bowen Zheng, Xiaohong Liu, et al.. (2022). Improving artificial intelligence pipeline for liver malignancy diagnosis using ultrasound images and video frames. Briefings in Bioinformatics. 24(1). 18 indexed citations

10.

Sang, Ye, et al.. (2021). Deep learning method for determining the surface elastic moduli of microstructured solids. Extreme Mechanics Letters. 44. 101226–101226. 24 indexed citations

11.

Gao, Song, et al.. (2021). Constitutive modeling and microstructure research on the deformation mechanism of Ti-6Al-4V alloy under hot forming condition. Journal of Alloys and Compounds. 892. 162128–162128. 53 indexed citations

12.

Sang, Ye, et al.. (2021). Deep learning method for predicting the mechanical properties of aluminum alloys with small data sets. Materials Today Communications. 28. 102570–102570. 39 indexed citations

13.

Sang, Ye, Bo Li, Qunyang Li, Hongping Zhao, & Xi‐Qiao Feng. (2019). Deep neural network method for predicting the mechanical properties of composites. Applied Physics Letters. 115(16). 112 indexed citations

14.

Sang, Ye, et al.. (2019). Torsion Instability of Anisotropic Cylindrical Tissues with Growth. Acta Mechanica Solida Sinica. 32(5). 621–632. 6 indexed citations

15.

Lin, Shao‐Zhen, Ye Sang, Guang‐Kui Xu, Bo Li, & Xi‐Qiao Feng. (2018). Dynamic Migration Modes of Collective Cells. Biophysical Journal. 115(9). 1826–1835. 71 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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