Yao Wang

8.8k total citations · 3 hit papers
246 papers, 6.3k citations indexed

About

Yao Wang is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Electrical and Electronic Engineering. According to data from OpenAlex, Yao Wang has authored 246 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Computer Vision and Pattern Recognition, 50 papers in Computational Mechanics and 37 papers in Electrical and Electronic Engineering. Recurrent topics in Yao Wang's work include Sparse and Compressive Sensing Techniques (41 papers), Image and Signal Denoising Methods (36 papers) and Advanced Image Fusion Techniques (16 papers). Yao Wang is often cited by papers focused on Sparse and Compressive Sensing Techniques (41 papers), Image and Signal Denoising Methods (36 papers) and Advanced Image Fusion Techniques (16 papers). Yao Wang collaborates with scholars based in China, United States and Macao. Yao Wang's co-authors include Deyu Meng, Jöern Ostermann, Qian Zhao, Xi-Le Zhao, Jincheng Huang, Zhu Liu, Jiangjun Peng, Zongben Xu, Yee Leung and Byrav Ramamurthy and has published in prestigious journals such as Angewandte Chemie International Edition, Applied Physics Letters and Bioinformatics.

In The Last Decade

Yao Wang

221 papers receiving 6.1k citations

Hit Papers

Video Processing and Communications 2001 2026 2009 2017 2001 2017 2010 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yao Wang China 38 2.5k 1.1k 1.1k 838 728 246 6.3k
Zhao Zhang China 46 3.8k 1.5× 779 0.7× 435 0.4× 1.2k 1.4× 566 0.8× 342 7.0k
Wei Chen China 38 1.5k 0.6× 849 0.8× 442 0.4× 399 0.5× 1.9k 2.5× 467 5.5k
Xin Yuan China 48 3.4k 1.3× 2.9k 2.6× 926 0.9× 1.7k 2.0× 851 1.2× 342 8.0k
Sheng Li China 42 1.9k 0.8× 502 0.5× 334 0.3× 403 0.5× 1.3k 1.8× 352 7.7k
Jinhui Tang China 68 13.3k 5.2× 1.0k 0.9× 1.0k 1.0× 1.9k 2.3× 374 0.5× 459 18.8k
Ming Li China 39 1.1k 0.5× 470 0.4× 579 0.5× 199 0.2× 1.0k 1.4× 450 7.9k
Mika Sirén Germany 12 2.8k 1.1× 385 0.3× 776 0.7× 576 0.7× 267 0.4× 17 5.9k
Tongliang Liu Australia 46 3.8k 1.5× 361 0.3× 344 0.3× 685 0.8× 270 0.4× 186 6.7k
Fei Sha China 42 3.6k 1.4× 346 0.3× 791 0.7× 367 0.4× 588 0.8× 218 9.0k
Bin Yu China 39 2.2k 0.9× 515 0.5× 324 0.3× 1.2k 1.4× 243 0.3× 157 6.8k

Countries citing papers authored by Yao Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yao Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yao Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Yao Wang. A scholar is included among the top collaborators of Yao 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 Yao Wang. Yao 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.
Liu, Jiapeng, et al.. (2025). A Probabilistic preference learning approach for multiple criteria ranking in dynamic decision context. European Journal of Operational Research. 330(2). 558–574.
2.
Zhan, Xin, Ming‐Sheng Wang, Yao Wang, et al.. (2025). Low temperature creep behavior of directionally solidified superalloys. Materials Today Communications. 45. 112212–112212.
5.
Peng, Jiangjun, et al.. (2024). Guaranteed matrix recovery using weighted nuclear norm plus weighted total variation minimization. Signal Processing. 227. 109706–109706. 1 indexed citations
6.
Wang, Yao, et al.. (2024). Nijenhuis-operator on Hom-Lie conformal algebras. Topology and its Applications. 344. 108817–108817. 3 indexed citations
7.
Zhao, Xi-Le, et al.. (2024). Snapshot Compressive Imaging Using Domain-Factorized Deep Video Prior. IEEE Transactions on Computational Imaging. 10. 93–102.
8.
Wang, Yao, et al.. (2023). Fuzzy clustering for feature extraction in wavelet-based fault gear identification of electrical machines. Journal of Intelligent & Fuzzy Systems. 46(1). 2415–2431.
9.
Wang, Ce, Shuai He, Yao Wang, et al.. (2023). Acoustic 3D trapping of microparticles in flowing liquid using circular cavity. Sensors and Actuators A Physical. 363. 114698–114698. 5 indexed citations
10.
Wang, Ce, et al.. (2023). Development of air-assisted atomization device for the delivery of cells in viscous biological ink prepared with sodium alginate. Review of Scientific Instruments. 94(4). 4 indexed citations
11.
Yao, Junping, et al.. (2023). A Spectral–Spatial Feature Rotation-Based Ensemble Method for Imbalanced Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–18. 3 indexed citations
12.
Liu, Sheng, Jinsong Leng, Xi-Le Zhao, et al.. (2023). Learnable Spatial-Spectral Transform-Based Tensor Nuclear Norm for Multi-Dimensional Visual Data Recovery. IEEE Transactions on Circuits and Systems for Video Technology. 34(5). 3633–3646. 8 indexed citations
13.
Wang, Yao, et al.. (2020). Hyperspectral and Multispectral Image Fusion via Nonlocal Low-Rank Tensor Decomposition and Spectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing. 58(11). 7654–7671. 39 indexed citations
14.
Zhao, Xi-Le, Wenhao Xu, Tai-Xiang Jiang, Yao Wang, & Michael K. Ng. (2020). Deep plug-and-play prior for low-rank tensor completion. Neurocomputing. 400. 137–149. 80 indexed citations
15.
Landsberg, J. M., et al.. (2020). Towards a geometric approach to Strassen’s asymptotic rank conjecture. Collectanea mathematica. 72(1). 63–86. 5 indexed citations
16.
Jiang, Tai-Xiang, Ting‐Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, & Yao Wang. (2017). A Novel Tensor-Based Video Rain Streaks Removal Approach via Utilizing Discriminatively Intrinsic Priors. 2818–2827. 120 indexed citations
17.
Wang, Yao, et al.. (2017). Compressive Sensing of Hyperspectral Images via Joint Tensor Tucker Decomposition and Weighted Total Variation Regularization. IEEE Geoscience and Remote Sensing Letters. 14(12). 2457–2461. 74 indexed citations
18.
Cao, Wenfei, Yao Wang, Jian Sun, et al.. (2016). Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 84 indexed citations
19.
Wang, Yao, Kyoko Yoshida, Joy Vink, et al.. (2014). Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation. Journal of the mechanical behavior of biomedical materials. 34. 18–26. 45 indexed citations
20.
Wang, Yao, et al.. (2005). Tables of Bounds for Distributions with Monotone Log-Odds Rate. Communications in Statistics - Simulation and Computation. 34(1). 1–20. 5 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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