Yizheng Wang

1.0k total citations · 2 hit papers
29 papers, 463 citations indexed

About

Yizheng Wang is a scholar working on Electrical and Electronic Engineering, Statistical and Nonlinear Physics and Mechanics of Materials. According to data from OpenAlex, Yizheng Wang has authored 29 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 9 papers in Statistical and Nonlinear Physics and 7 papers in Mechanics of Materials. Recurrent topics in Yizheng Wang's work include Model Reduction and Neural Networks (9 papers), Electric Power System Optimization (6 papers) and Numerical methods in engineering (6 papers). Yizheng Wang is often cited by papers focused on Model Reduction and Neural Networks (9 papers), Electric Power System Optimization (6 papers) and Numerical methods in engineering (6 papers). Yizheng Wang collaborates with scholars based in China, Germany and Australia. Yizheng Wang's co-authors include Timon Rabczuk, Thomas Olofsson, Bokai Liu, Weizhuo Lu, Yinghua Liu, Cosmin Anitescu, Timon Rabczuk, Mohammad Sadegh Eshaghi, Jinshuai Bai and Yinghua Liu and has published in prestigious journals such as Developmental Cell, Computer Methods in Applied Mechanics and Engineering and Renewable Energy.

In The Last Decade

Yizheng Wang

26 papers receiving 440 citations

Hit Papers

Kolmogorov–Arnold-Informed neural network: A physics-info... 2024 2026 2025 2024 2025 10 20 30 40 50

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yizheng Wang China 13 134 83 69 60 55 29 463
Shuai Shao China 12 243 1.8× 15 0.2× 86 1.2× 47 0.8× 85 1.5× 32 557
Liangwen Wang China 10 41 0.3× 92 1.1× 47 0.7× 114 1.9× 31 0.6× 71 406
Xiaoyu Xie China 10 72 0.5× 67 0.8× 50 0.7× 279 4.7× 28 0.5× 29 566
Xiaoyu Zhao China 11 22 0.2× 76 0.9× 20 0.3× 82 1.4× 22 0.4× 52 399
Yuxi Xie United States 10 22 0.2× 90 1.1× 92 1.3× 88 1.5× 68 1.2× 31 465
Mohamed E. Ghoneim Egypt 13 36 0.3× 23 0.3× 15 0.2× 176 2.9× 18 0.3× 27 471
Shuyue Wang China 12 127 0.9× 30 0.4× 33 0.5× 72 1.2× 64 1.2× 39 480
Viktor Beneš Czechia 11 15 0.1× 33 0.4× 20 0.3× 87 1.4× 28 0.5× 70 477
John Jasa United States 14 31 0.2× 33 0.4× 36 0.5× 28 0.5× 38 0.7× 30 584

Countries citing papers authored by Yizheng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yizheng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yizheng Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Yizheng Wang. A scholar is included among the top collaborators of Yizheng Wang 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 Yizheng Wang. Yizheng Wang 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.
Wang, Yizheng, Yizheng Wang, Yuting Wang, et al.. (2025). A rapid population-based iterated greedy for distributed blocking group flowshop scheduling with delivery time windows under multiple processing time scenarios. Computers & Industrial Engineering. 202. 110949–110949. 1 indexed citations
2.
Bai, Jinshuai, Yizheng Wang, Yinghua Liu, et al.. (2025). Energy-based physics-informed neural network for frictionless contact problems under large deformation. Computer Methods in Applied Mechanics and Engineering. 437. 117787–117787. 16 indexed citations
3.
Liu, Bokai, Pengju Liu, Yizheng Wang, et al.. (2025). Explainable machine learning for multiscale thermal conductivity modeling in polymer nanocomposites with uncertainty quantification. Composite Structures. 370. 119292–119292. 16 indexed citations
4.
Eshaghi, Mohammad Sadegh, et al.. (2025). Variational Physics-informed Neural Operator (VINO) for solving partial differential equations. Computer Methods in Applied Mechanics and Engineering. 437. 117785–117785. 34 indexed citations breakdown →
5.
Anitescu, Cosmin, et al.. (2025). Energy-based methods for solving forward and inverse linear elasticity problems in 2D structures. Computers & Structures. 316. 107899–107899. 1 indexed citations
6.
Bai, Jinshuai, Yizheng Wang, Hyogu Jeong, et al.. (2025). Towards the future of physics- and data-guided AI frameworks in computational mechanics. Acta Mechanica Sinica. 41(7). 3 indexed citations
7.
Wang, Yizheng, Jinshuai Bai, Cosmin Anitescu, et al.. (2024). Kolmogorov–Arnold-Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov–Arnold Networks. Computer Methods in Applied Mechanics and Engineering. 433. 117518–117518. 53 indexed citations breakdown →
8.
Wang, Yizheng, et al.. (2024). DCEM: A deep complementary energy method for linear elasticity. International Journal for Numerical Methods in Engineering. 125(24). 13 indexed citations
9.
Yu, Yang, et al.. (2024). Short-term load forecasting based on CEEMDAN and dendritic deep learning. Knowledge-Based Systems. 294. 111729–111729. 24 indexed citations
10.
Eshaghi, Mohammad Sadegh, et al.. (2024). Applications of scientific machine learning for the analysis of functionally graded porous beams. Neurocomputing. 619. 129119–129119. 14 indexed citations
12.
Bai, Jinshuai, et al.. (2024). A robust radial point interpolation method empowered with neural network solvers (RPIM-NNS) for nonlinear solid mechanics. Computer Methods in Applied Mechanics and Engineering. 429. 117159–117159. 15 indexed citations
13.
Wang, Yizheng, et al.. (2024). Survey of Deep Learning Applications in WiFi Localization. 517–522. 2 indexed citations
15.
Liu, Yinghua, et al.. (2023). BINN: A deep learning approach for computational mechanics problems based on boundary integral equations. Computer Methods in Applied Mechanics and Engineering. 410. 116012–116012. 30 indexed citations
16.
Wang, Yizheng, et al.. (2023). Dcm: Deep Complementary Energy Method Based on the Principle of Minimum Complementary Energy. SSRN Electronic Journal. 1 indexed citations
17.
Wang, Hongliang, et al.. (2022). Research on Evaluation of Multi-Timescale Flexibility and Energy Storage Deployment for the High-Penetration Renewable Energy of Power Systems. Computer Modeling in Engineering & Sciences. 134(2). 1137–1158. 3 indexed citations
19.
Yi, Cong, Jingjing Tong, Yizheng Wang, et al.. (2017). Formation of a Snf1-Mec1-Atg1 Module on Mitochondria Governs Energy Deprivation-Induced Autophagy by Regulating Mitochondrial Respiration. Developmental Cell. 41(1). 59–71.e4. 61 indexed citations
20.
Wang, Yizheng, Lefei Li, & Liuqing Yang. (2013). Intelligent Human Resource Planning System in a Large Petrochemical Enterprise. IEEE Intelligent Systems. 28(4). 102–106. 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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