Houpu Yao

758 total citations
21 papers, 560 citations indexed

About

Houpu Yao is a scholar working on Artificial Intelligence, Civil and Structural Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Houpu Yao has authored 21 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Civil and Structural Engineering and 6 papers in Statistical and Nonlinear Physics. Recurrent topics in Houpu Yao's work include Model Reduction and Neural Networks (6 papers), Structural Health Monitoring Techniques (4 papers) and Non-Destructive Testing Techniques (3 papers). Houpu Yao is often cited by papers focused on Model Reduction and Neural Networks (6 papers), Structural Health Monitoring Techniques (4 papers) and Non-Destructive Testing Techniques (3 papers). Houpu Yao collaborates with scholars based in United States, China and United Kingdom. Houpu Yao's co-authors include Yongming Liu, Yi Ren, Yang Yu, Ruijin Cang, Yang Jiao, Yi Gao, Yutian Pang, Ze Ji, Min Xia and Feng Xu and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, Neurocomputing and Engineering Fracture Mechanics.

In The Last Decade

Houpu Yao

20 papers receiving 541 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Houpu Yao United States 10 177 134 102 86 84 21 560
Aldo Ghisi Italy 16 225 1.3× 136 1.0× 186 1.8× 72 0.8× 61 0.7× 65 916
Hongwei Guo China 10 293 1.7× 150 1.1× 299 2.9× 108 1.3× 43 0.5× 32 809
Hyuk Lee Australia 10 289 1.6× 76 0.6× 130 1.3× 85 1.0× 74 0.9× 19 685
Chunlin Gong China 18 167 0.9× 153 1.1× 147 1.4× 132 1.5× 37 0.4× 101 888
Nguyen Dong Anh Vietnam 17 400 2.3× 102 0.8× 136 1.3× 77 0.9× 21 0.3× 81 721
Jun Tao China 12 48 0.3× 82 0.6× 63 0.6× 38 0.4× 52 0.6× 27 563
Hengyang Li China 14 117 0.7× 134 1.0× 272 2.7× 110 1.3× 39 0.5× 27 712
Yuxi Xie United States 10 92 0.5× 88 0.7× 90 0.9× 82 1.0× 105 1.3× 31 465
Jean Louis Duval France 10 83 0.5× 169 1.3× 143 1.4× 36 0.4× 19 0.2× 31 487
Jan N. Fuhg United States 15 151 0.9× 186 1.4× 341 3.3× 93 1.1× 78 0.9× 27 974

Countries citing papers authored by Houpu Yao

Since Specialization
Citations

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

Fields of papers citing papers by Houpu Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Houpu Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Houpu Yao. A scholar is included among the top collaborators of Houpu 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 Houpu Yao. Houpu Yao 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.
2.
Yao, Houpu, et al.. (2022). Fracture pattern prediction with random microstructure using a physics-informed deep neural networks. Engineering Fracture Mechanics. 268. 108497–108497. 11 indexed citations
3.
4.
Yao, Houpu, et al.. (2021). Self-validating high-g accelerometers through data-driven methods. Sensors and Actuators A Physical. 328. 112803–112803. 9 indexed citations
5.
Yao, Houpu, et al.. (2020). On Fault Diagnosis for High-G Accelerometers via Data-Driven Models. IEEE Sensors Journal. 21(2). 1359–1368. 20 indexed citations
6.
Yao, Houpu, Yi Gao, & Yongming Liu. (2020). FEA-Net: A physics-guided data-driven model for efficient mechanical response prediction. Computer Methods in Applied Mechanics and Engineering. 363. 112892–112892. 60 indexed citations
7.
Gao, Yi, et al.. (2020). Physics-based Deep Learning for Probabilistic Fracture Analysis of Composite Materials. AIAA Scitech 2020 Forum. 5 indexed citations
8.
Yu, Yang, Houpu Yao, & Yongming Liu. (2020). Structural dynamics simulation using a novel physics-guided machine learning method. Engineering Applications of Artificial Intelligence. 96. 103947–103947. 90 indexed citations
9.
Yu, Yang, Houpu Yao, & Yongming Liu. (2019). Aircraft dynamics simulation using a novel physics-based learning method. Aerospace Science and Technology. 87. 254–264. 44 indexed citations
10.
Yao, Houpu, Yi Ren, & Yongming Liu. (2019). FEA-Net: A Deep Convolutional Neural Network With PhysicsPrior For Efficient Data Driven PDE Learning. AIAA Scitech 2019 Forum. 8 indexed citations
11.
Yao, Houpu, et al.. (2019). Low-cost Measurement of Industrial Shock Signals via Deep Learning Calibration. ORCA Online Research @Cardiff (Cardiff University). 64. 2892–2896. 5 indexed citations
12.
Yu, Yang, Houpu Yao, & Yongming Liu. (2019). A Hybrid Learning Approach for the Simulation of Aircraft Dynamical Systems. AIAA Scitech 2019 Forum. 1 indexed citations
13.
Yao, Houpu, et al.. (2019). A Deep Learning Approach to Recover High-g Shock Signals From the Faulty Accelerometer. IEEE Sensors Journal. 20(4). 1761–1769. 7 indexed citations
14.
Pang, Yutian, et al.. (2019). A Recurrent Neural Network Approach for Aircraft Trajectory Prediction with Weather Features From Sherlock. AIAA Aviation 2019 Forum. 41 indexed citations
15.
Cang, Ruijin, Houpu Yao, & Yi Ren. (2019). One-shot generation of near-optimal topology through theory-driven machine learning. Computer-Aided Design. 109. 12–21. 55 indexed citations
16.
17.
Yao, Houpu, et al.. (2018). A nonlinear dynamic model and parameters identification method for predicting the shock pulse of rubber waveform generator. International Journal of Impact Engineering. 120. 1–15. 17 indexed citations
18.
Yu, Yang, Houpu Yao, & Yongming Liu. (2018). Physics-based Learning for Aircraft Dynamics Simulation. Annual Conference of the PHM Society. 10(1). 17 indexed citations
19.
Cang, Ruijin, Houpu Yao, & Yi Ren. (2018). One-Shot Optimal Topology Generation through Theory-Driven Machine Learning.. 1 indexed citations
20.
Yao, Houpu, et al.. (2016). Impressionist: A 3D Peekaboo Game for Crowdsourcing Shape Saliency. 6 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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