Liang Hou

3.9k total citations · 1 hit paper
147 papers, 2.8k citations indexed

About

Liang Hou is a scholar working on Mechanical Engineering, Control and Systems Engineering and Automotive Engineering. According to data from OpenAlex, Liang Hou has authored 147 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Mechanical Engineering, 24 papers in Control and Systems Engineering and 18 papers in Automotive Engineering. Recurrent topics in Liang Hou's work include Advanced machining processes and optimization (12 papers), Product Development and Customization (12 papers) and Quality Function Deployment in Product Design (11 papers). Liang Hou is often cited by papers focused on Advanced machining processes and optimization (12 papers), Product Development and Customization (12 papers) and Quality Function Deployment in Product Design (11 papers). Liang Hou collaborates with scholars based in China, United States and United Kingdom. Liang Hou's co-authors include Samuel H. Huang, Peng Liu, Xiangjian Bu, Yun Chen, Jianxin Jiao, Huaizhong Li, Heng Zhou, Shaojie Wang, Shaogan Ye and Hesheng Tang and has published in prestigious journals such as The Science of The Total Environment, Journal of Agricultural and Food Chemistry and Scientific Reports.

In The Last Decade

Liang Hou

123 papers receiving 2.7k citations

Hit Papers

Additive manufacturing and its societal impact: a literat... 2012 2026 2016 2021 2012 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liang Hou China 19 1.4k 1.2k 692 619 238 147 2.8k
Andres L. Carrano United States 18 467 0.3× 1.0k 0.9× 383 0.6× 419 0.7× 222 0.9× 57 2.7k
Weihong Guo United States 30 485 0.4× 660 0.6× 737 1.1× 200 0.3× 110 0.5× 128 2.7k
Aydin Nassehi United Kingdom 28 506 0.4× 1.1k 1.0× 2.4k 3.4× 262 0.4× 149 0.6× 123 3.8k
Zhenyu Kong United States 33 938 0.7× 1.4k 1.2× 1.1k 1.6× 479 0.8× 34 0.1× 121 3.3k
Nita Yodo United States 21 903 0.7× 396 0.3× 341 0.5× 236 0.4× 122 0.5× 62 2.1k
Yongsheng Ma Canada 35 999 0.7× 1.1k 0.9× 1.5k 2.2× 262 0.4× 127 0.5× 183 3.9k
Shuyou Zhang China 24 345 0.3× 1.0k 0.9× 552 0.8× 273 0.4× 60 0.3× 264 2.6k
Jin Wang China 36 660 0.5× 2.0k 1.7× 230 0.3× 441 0.7× 78 0.3× 156 4.2k
Bin He China 28 205 0.2× 603 0.5× 819 1.2× 328 0.5× 398 1.7× 159 2.6k
Behrooz Arezoo Iran 26 195 0.1× 1.0k 0.9× 1.0k 1.5× 322 0.5× 80 0.3× 83 2.5k

Countries citing papers authored by Liang Hou

Since Specialization
Citations

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

Fields of papers citing papers by Liang Hou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liang Hou

This figure shows the co-authorship network connecting the top 25 collaborators of Liang Hou. A scholar is included among the top collaborators of Liang Hou 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 Liang Hou. Liang Hou 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, Shaojie, et al.. (2025). Multi-sensor data fusion and deep learning-based prediction of excavator bucket fill rates. Automation in Construction. 171. 106008–106008. 3 indexed citations
2.
Zhao, Aiju, Yuping Liu, Xiyong Chen, et al.. (2025). Single-Cell Transcriptome Reveals the Cellular Response to PEG-Induced Stress in Wheat Leaves. Journal of Agricultural and Food Chemistry. 73(18). 10764–10777.
3.
Hou, Liang, et al.. (2025). Generative adversarial network for stress-minimizing topology optimization. International Journal of Mechanics and Materials in Design. 21(6). 2013–2030.
4.
Chen, Yunmin, et al.. (2025). Multi-material topology optimisation with design-dependent loads using the ordered EAMP quadratic penalty method. Journal of Engineering Design. 37(3). 653–680. 1 indexed citations
5.
Liu, Ying, et al.. (2025). Agile conceptual design and validation based on multi-source product data and large language models: a review, framework, and outlook. Journal of Engineering Design. 36(4). 473–503. 4 indexed citations
6.
Hou, Liang, et al.. (2025). Model reconstruction and update method for dynamic prediction of loader loading resistance using deep incremental learning. Engineering Applications of Artificial Intelligence. 153. 110910–110910. 2 indexed citations
7.
Wang, Shaojie, et al.. (2024). Parameter Estimation of a Valve-Controlled Cylinder System Model Based on Bench Test and Operating Data Fusion. Chinese Journal of Mechanical Engineering. 37(1). 1 indexed citations
8.
Pan, Yongjun, et al.. (2024). Pitch motion suppression of electric vehicle active suspensions based on multibody dynamics. Mechanism and Machine Theory. 198. 105667–105667. 6 indexed citations
9.
Wang, Shaojie, et al.. (2024). Application of physics-informed machine learning for excavator working resistance modeling. Mechanical Systems and Signal Processing. 209. 111117–111117. 9 indexed citations
10.
Wang, Shaojie, et al.. (2024). Research on predictive modeling method of loader working resistance in a sensor-less environment. Engineering Applications of Artificial Intelligence. 138. 109263–109263. 1 indexed citations
11.
Wang, Shaojie, et al.. (2023). Fast Estimation of Loader’s Shovel Load Volume by 3D Reconstruction of Material Piles. Chinese Journal of Mechanical Engineering. 36(1). 4 indexed citations
12.
Hou, Liang, et al.. (2023). Predictive modeling of loader's working resistance measurement based on multi-sourced parameter data. Automation in Construction. 149. 104805–104805. 12 indexed citations
13.
Hou, Liang, et al.. (2023). Uncertainty modeling and applications for operating data-driven inverse design. Journal of Engineering Design. 34(2). 81–110. 5 indexed citations
14.
Cao, Qi, Huawei Shen, Yunfan Wu, et al.. (2023). Adversarial camouflage for node injection attack on graphs. Information Sciences. 649. 119611–119611. 16 indexed citations
15.
Zheng, Guangming, Yun Chen, Liang Hou, et al.. (2023). Multi-objective optimization of surface morphology using fractal and multi-fractal analysis for dry milling of AISI 4340. Measurement. 222. 113574–113574. 4 indexed citations
17.
Zhang, Donghui, Lifu Zhang, Xuejian Sun, et al.. (2022). A New Method for Calculating Water Quality Parameters by Integrating Space–Ground Hyperspectral Data and Spectral-In Situ Assay Data. Remote Sensing. 14(15). 3652–3652. 12 indexed citations
18.
Ye, Shaogan, Junhui Zhang, Bing Xu, et al.. (2020). A theoretical dynamic model to study the vibration response characteristics of an axial piston pump. Mechanical Systems and Signal Processing. 150. 107237–107237. 83 indexed citations
19.
Chen, Yun, Huaizhong Li, Liang Hou, Jun Wang, & Xiangjian Bu. (2018). An intelligent chatter detection method based on EEMD and feature selection with multi-channel vibration signals. Measurement. 127. 356–365. 76 indexed citations
20.
Hou, Liang. (2006). Application of rough sets theory in digital image watermarking. Journal of Computer Applications. 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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