Wen Yao

6.0k total citations · 2 hit papers
241 papers, 4.0k citations indexed

About

Wen Yao is a scholar working on Artificial Intelligence, Aerospace Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Wen Yao has authored 241 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Artificial Intelligence, 54 papers in Aerospace Engineering and 36 papers in Computational Theory and Mathematics. Recurrent topics in Wen Yao's work include Advanced Multi-Objective Optimization Algorithms (31 papers), Model Reduction and Neural Networks (27 papers) and Probabilistic and Robust Engineering Design (27 papers). Wen Yao is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (31 papers), Model Reduction and Neural Networks (27 papers) and Probabilistic and Robust Engineering Design (27 papers). Wen Yao collaborates with scholars based in China, United States and Netherlands. Wen Yao's co-authors include Xiaoqian Chen, Michel van Tooren, Chao‐Hsien Chu, Li Zang, Weien Zhou, Wei Peng, Wencai Luo, Zhiqiang Gong, Jian Guo and Xü Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Wen Yao

215 papers receiving 3.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles

2011 386 citations Wen Yao, Xiaoqian Chen et al. profile →
Self-adaptive loss balanced Physics-informed neural networks

2022 242 citations Wei Peng, Xü Liu et al. Neurocomputing profile →

Peers

Wen Yao

AI

SPU

CTM

AE

SNP

Lei Wang China

Giuseppe C. Calafiore Italy

Felipe Viana United States

András Sóbester United Kingdom

Richard Everson United Kingdom

Virginia Torczon United States

Daniel W. Apley United States

Antonio Vicino Italy

Gerhard Venter South Africa

James C. Spall United States

Lei Wang China

Wen Yao

674 ×0.8

AI

241 ×0.3

SPU

248 ×0.4

CTM

309 ×0.5

AE

514 ×1.0

SNP

Citations per year, relative to Wen Yao Wen Yao (= 1×) peers Lei Wang

Countries citing papers authored by Wen Yao

Since Specialization

Citations

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

Fields of papers citing papers by Wen Yao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wen Yao

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Chen, Xianqi, et al.. (2025). Mixed integer programming modeling for the satellite three-dimensional component assignment and layout optimization problem. Chinese Journal of Aeronautics. 38(6). 103415–103415.

2.

Yao, Wen, et al.. (2025). Image-to-Image Bayesian Flow Networks With Structurally Informative Priors. IEEE Transactions on Image Processing. 34. 4968–4982.

3.

Wang, Donghua, et al.. (2024). AdvOps: Decoupling adversarial examples. Pattern Recognition. 149. 110252–110252. 1 indexed citations

4.

Zhang, Yunyang, et al.. (2024). Towards sparse sensor annotations: Uncertainty-based active transfer learning for airfoil flow field prediction. Chinese Journal of Aeronautics. 37(12). 87–98. 3 indexed citations

5.

Li, Xingchen, et al.. (2024). PEGNN: A physics embedded graph neural network for out-of-distribution temperature field reconstruction. International Journal of Thermal Sciences. 207. 109393–109393. 4 indexed citations

6.

Zhao, Dong, et al.. (2024). Stochastic measurement-based multi-cloud consolidation for efficient resource distribution. Measurement. 242. 115973–115973. 1 indexed citations

7.

Zheng, Xiaohu, Wen Yao, Zhiqiang Gong, & Xiaoya Zhang. (2024). Learnable quantile polynomial chaos expansion: An uncertainty quantification method for interval reliability analysis. Reliability Engineering & System Safety. 245. 110036–110036. 9 indexed citations

8.

Yao, Wen, et al.. (2024). Adversarial patch-based false positive creation attacks against aerial imagery object detectors. Neurocomputing. 579. 127431–127431. 8 indexed citations

9.

Zhu, Xiaozhou, et al.. (2024). Fixed-time trajectory tracking control of a quadrotor UAV under time-varying wind disturbances: theory and experimental validation. Measurement Science and Technology. 35(8). 86205–86205. 8 indexed citations

10.

Wang, Donghua, Wen Yao, Tingsong Jiang, et al.. (2024). An invisible, robust copyright protection method for DNN-generated content. Neural Networks. 177. 106391–106391.

11.

Yao, Wen, et al.. (2024). Machine learning-based multi-objective optimization of thermo-mechanical field of anisotropic plates. Thin-Walled Structures. 207. 112718–112718. 5 indexed citations

12.

Yao, Wen, et al.. (2024). Black-box adversarial patch attacks using differential evolution against aerial imagery object detectors. Engineering Applications of Artificial Intelligence. 137. 109141–109141. 2 indexed citations

13.

Zhang, Jun, et al.. (2023). RBUE: a ReLU-based uncertainty estimation method for convolutional neural networks. Complex & Intelligent Systems. 9(5). 4735–4749. 1 indexed citations

14.

Yao, Wen, et al.. (2023). A multi-objective memetic algorithm for automatic adversarial attack optimization design. Neurocomputing. 547. 126318–126318. 4 indexed citations

15.

Yao, Wen, et al.. (2023). Bayesian evolutionary optimization for crafting high-quality adversarial examples with limited query budget. Applied Soft Computing. 142. 110370–110370. 12 indexed citations

16.

Zheng, Xiaohu, et al.. (2023). Algorithms for Bayesian network modeling and reliability inference of complex multistate systems with common cause failure. Reliability Engineering & System Safety. 241. 109663–109663. 18 indexed citations

17.

Liu, Xü, Wen Yao, Wei Peng, & Weien Zhou. (2023). Bayesian physics-informed extreme learning machine for forward and inverse PDE problems with noisy data. Neurocomputing. 549. 126425–126425. 24 indexed citations

18.

Zheng, Xiaohu, et al.. (2023). Parameterized coefficient fine-tuning-based polynomial chaos expansion method for sphere-biconic reentry vehicle reliability analysis and design. Reliability Engineering & System Safety. 240. 109568–109568. 6 indexed citations

19.

Yao, Wen, et al.. (2023). Predicting the temperature field of composite materials under a heat source using deep learning. Composite Structures. 321. 117320–117320. 7 indexed citations

20.

Zhang, Yunyang, et al.. (2023). Uncertainty guided ensemble self-training for semi-supervised global field reconstruction. Complex & Intelligent Systems. 10(1). 469–483. 3 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