Biography
Licheng ZHOU, Professor and Doctoral Supervisor, earned his Bachelor's degree from the University of Science and Technology of China in 2010 and his Ph.D. from Peking University in 2015. He is a recipient of the National Natural Science Foundation for Young Scientists (Type B) [formerly the Excellent Young Scientists Fund] (2025). He currently serves as the Vice Chair of the AI Experimental Mechanics Group of the Chinese Society of Theoretical and Applied Mechanics and the Deputy Secretary-General of the Guangdong Society of Theoretical and Applied Mechanics. He also holds editorial board positions, including Youth Editorial Board Member for Acta Mechanica Sinica(JCR Q1), Theoretical and Applied Mechanics Letters(JCR Q2), and Applied Mathematics and Mechanics(Chinese Core), and Editorial Board Member for Experimental Mechanics(Chinese Core). His research focuses on AI-based structural health monitoring technology and the integrated design of electromagnetic wave-transparent/stealth structures, specifically developing AI-driven methods to extract health indicators from monitoring data of large engineering structures and creating efficient multi-objective optimization design methods for electromagnetic/mechanical structures. His work supports major bridges in the Greater Bay Area and relevant national defense units. He has led four National Natural Science Foundation projects, one Guangdong Provincial Natural Science Foundation project, one Guangzhou Science and Technology Plan project, and one China Postdoctoral Science Foundation project, and has participated as a key member in several key national and provincial projects. To date, he has published over 30 SCI papers as first or corresponding author, with several appearing in flagship journals such as Composites Science and Technology, Engineering Structures, and IEEE Transactions on Antennas and Propagation. He has received awards including the Second Prize of the Guangdong Provincial Science and Technology Progress Award and the Second Prize of the Science and Technology Award from the Guangdong Provincial Society of Civil and Architectural Engineering.
Education
Sep 2010-Jul 2015, Ph.D. in Solid Mechanics, Peking University
Oct 2012-Oct 2013, Joint Ph.D. Training in Mechanical Science and Engineering, Nagoya University
Sep 2006-Jul 2010, B.S. in Theoretical and Applied Mechanics, University of Science and Technology of China
Research Areas
1. AI and Robotics-based Structural Health Monitoring Technology This research direction integrates intelligent robots (such as unmanned aerial vehicles and climbing robots) to achieve intelligent collection of multi-source mechanical response data from engineering structures. It utilizes deep learning algorithms to extract damage-sensitive features correlated with structural health status from spatially and temporally sparse monitoring data, thereafter establishing effective damage identification methods. The outcomes are applicable to the health monitoring of large-scale bridges, high-rise buildings, dams, mechanical equipment, and aerospace structures. 2. AI-driven Integrated Design of Electromagnetic Wave-transparent/Stealth Structures This research focuses on employing deep learning to establish multi-objective optimization design methods for electromagnetic wave-transparent/stealth structures, addressing the inefficiency and ineffectiveness of traditional design approaches. The results can be applied to the design of key components such as new-generation aircraft smart skins, and radomes for missiles and rockets in the aerospace and defense sectors.
Courses Taught
1. Theoretical Mechanics (Compulsory Course)
2. Experimental Mechanics (Compulsory Course)
3. Machine Learning (Elective Course)
Selected Publications
- Huang, Xuhao;Liu, Zejia;Lu, Yonghui;Yang, Bao;Zhou, Licheng;Jiang, Zhenyu;Liu, Yiping;Tang, Liqun,An interactive multi-task learning model for multi-channel strain data reconstruction in SHM,Engineering Structures,2026
- Zhang, Ge;Sun, Hui;Liu, Zejia;Zhou, Licheng;Chen, Gongfa;Tang, Liqun;Cui, Fangsen,Artificial Intelligence-Based Damage Identification Method Using Principal Component Analysis with Spatial and Multi-Scale Temporal Windows,International Journal of Computational Methods,2025
- Xian, Zhaoquan;Wang, Zekai;Liu, Zejia;Zhou, Licheng;Yang, Bao;Jiang, Zhenyu;Liu, Yiping;Tang, Liqun,Design Method of Dual-Band High-Temperature Streamlined Radomes Accelerated by Artificial Intelligence,IEEE Antennas and Wireless Propagation Letters,2025
- Lu, Yonghui;Tang, Liqun;Liu, Zejia;Zhou, Licheng;Yang, Bao;Jiang, Zhenyu;Liu, Yiping,Unsupervised damage localization method based on GAN-BiLSTM response modeling,Engineering Structures,2025
- Liu, Jun;Li, Yuqin;Dong, Shoubin;Zhou, Licheng;Liu, Zejia;Yang, Bao;Jiang, Zhenyu;Liu, Yiping;Tang, Liqun,Overloaded vehicle identification for long-span bridges based on physics-informed multi-task deep learning leveraging influence line,Engineering Structures,2025
- Chen, Chengbin;Tang, Liqun;Xiao, Qingkai;Zhou, Licheng;Liu, Zejia;Liu, Yiping;Jiang, Zhenyu;Yang, Bao,Damage localization using a deep learning-based response modeling method,COMPUTERS & STRUCTURES,2025
- Xiao, Qingkai;Liu Yiping;Chen, Chengbin;Zhou, Licheng;Liu Zejia;Jiang, Zhenyu,Data-driven time-variant reliability assessment of bridge girders based on deep learning,Mechanics of Advanced Materials and Structures,2024
- Lu, Yonghui;Tang, Liqun;Chen, Chengbin;Zhou, Licheng;Liu, Zejia;Liu, Yiping;Jiang, Zhenyu;Yang, Bao,Unsupervised structural damage assessment method based on response correlations,Engineering Structures,2024
- Wang, Zekai;Tang, Liqun;Liu, Bingxun;Zhou, Licheng;Liu, Zejia;Liu, Yiping;Jiang, Zhenyu;Yang, Bao,Multifunctional Design for Arbitrary Multiband Radome Wall Accelerated by Artificial Intelligence,AIAA Journal,2024
- Xiao, Qingkai;Liu, Yiping;Chen, Chengbin;Zhou, Licheng;Liu, Zejia;Jiang, Zhenyu;Yang, Bao;Tang, Liqun,Time-variant reliability assessment for bridge structures based on deep learning and regular vine copula models,Measurement,2024
- Lu, Yonghui;Tang, Liqun;Liu, Zejia;Zhou, Licheng;Yang, Bao;Jiang, Zhenyu;Liu, Yiping,Unsupervised quantitative structural damage identification method based on BiLSTM networks and probability distribution model,Journal of Sound and Vibration,2024
- He, Kai;Liao, Huanchen;Liu, Zejia;Liu, Yiping;Tang, Liqun;Yang, Bao;Zhou, Licheng;Jiang, Zhenyu,Reinforcing efficiency of nanophases with various geometric shapes on interfacial bonding in multiscale composites,Composites Part A: Applied Science and Manufacturing,2023
- Chen, Chengbin;Tang, Liqun;Lu, Yonghui;Zhou, Licheng;Liu, Zejia;Liu, Yiping;Jiang, Zhenyu;Yang, Bao,Temperature-induced response reconstruction method based on DL-AR model and attention mechanism,Structures,2023
- Chen, Chengbin;Tang, Liqun;Lu, Yonghui;Wang, Yong;Liu, Zejia;Liu, Yiping;Zhou, Licheng;Jiang, Zhenyu;Yang, Bao,Reconstruction of long-term strain data for structural health monitoring with a hybrid deep-learning and autoregressive model considering thermal effects,Engineering Structures,2023
- Xiao, Qingkai;Chen, Chengbin;Liu, Zejia;Zhou, Licheng;Liu, Yiping;Jiang, Zhenyu;Yang, Bao;Tang, Liqun,Temperature-induced response reconstruction for the dynamic reliability assessment of bridge girders,Structures,2023
- Xu Jiajie;Tang Liqun;Liu Yiping;Zhou Licheng;Chen Jinming;Jiang Zhenyu;Liu Zejia;Yang Bao,Hybridization effects on ballistic impact behavior of carbon/ aramid fiber reinforced hybrid composite,International Journal of Impact Engineering,2023
- Lu, Yonghui;Tang, Liqun;Chen, Chengbin;Zhou, Licheng;Liu, Zejia;Liu, Yiping;Jiang, Zhenyu;Yang, Bao,Reconstruction of structural long-term acceleration response based on BiLSTM networks,Engineering Structures,2023
- Wang, Zekai;Tang, Liqun;Zhou, Licheng;Jiang, Zhenyu;Liu, Zejia;Liu, Yiping,Methodology to Design Variable-Thickness Streamlined Radomes With Graded Dielectric Multilayered Wall,IEEE Transactions on Antennas and Propagation,2021
- Zhang Ge;Tang Liqun;Liu Zejia;Zhou Licheng;Liu Yiping;Jiang Zhenyu;Chen Jingsong;Sun Shuhang,Enhanced features in principal component analysis with spatial and temporal windows for damage identification,Inverse Problems in Science and Engineering,2021
- Zhang, Ge;Tang, Liqun;Liu, Zejia;Zhou, Licheng;Liu, Yiping;Jiang, Zhenyu,Machine-learning-based damage identification methods with features derived from moving principal component analysis,Mechanics of Advanced Materials and Structures,2020
- Zhang, Ge;Tang, Liqun;Zhou, Licheng;Liu, Zejia;Liu, Yiping;Jiang, Zhenyu,Principal Component Analysis Method with Space and Time Windows for Damage Detection,Sensors (Switzerland),2019
- Zhou, Licheng;Wang, Peiyu;Pei, Yongmao;Zeng, Anmin;Tang, Liqun;Liu, Zejia;Liu, Yiping;Jiang, Zhenyu;Fang, Daining,Design and characterization for dual-band and multi-band A sandwich composite radome walls,Composites Science and Technology,2017
- Zhou, Licheng;Liu, Zejia;Tang, Liqun;Pei, Yongmao,Design and characterization for a high-temperature dual-band radome wall structure for airborne applications,Materials and Design,2017
- Zhou, Licheng;Ju, Yang;Wang, Peiyu;Pei, Yongmao,Fast and stable integration method for the aperture admittance of an open-ended coaxial probe terminated into low-loss dielectrics,Progress in Electromagnetics Research M,2017
- Wang, Peiyu;Pei, Yongmao.;Zhou, Licheng,Near-field microwave identification and quantitative evaluation of liquid ingress in honeycomb sandwich structures,NDT & E International,2016
|
