Assoc. Prof. Dr. Lei Wang | Automatic Control Systems | Best Researcher Award

Assoc. Prof. Dr. Lei Wang | Automatic Control Systems | Best Researcher Award

Wuxi University, China.

Dr. Wang Lei is an Associate Professor at Wuxi University, specializing in intelligent control systems. With a strong background in artificial intelligence applications in automation, he has led over 10 major research projects, published more than 30 peer-reviewed papers, and holds 20+ patents and 11 software copyrights. He has international training experience in Thailand, Taiwan, Poland, and the UK, enriching his global academic perspective.

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πŸŽ“ Education

Dr. Wang Lei pursued extensive academic training, including joint doctoral programs funded by China’s national β€œ111 Plan”, conducting research in institutions like Green Mountain University (Poland) and the University of Southampton (UK). His master's studies included training at Prince Songkhla University (Thailand) and Yunlin University of Science and Technology (Taiwan).

πŸ’Ό Experience

Currently an Associate Professor at Wuxi University, Wang Lei has spearheaded numerous provincial and national research projects, including collaborations with the Ministry of Education, Wuxi Science and Technology Bureau, and the National Natural Science Foundation of China. His editorial roles include reviewing for journals like International Journal of Robust and Nonlinear Control and Security and Communication Networks.

πŸ”¬ Research Interests

His research focuses on the application of artificial intelligence in automatic control systems, covering areas such as iterative learning control, dynamic observers, fuzzy systems, and actuator fault tolerance.

πŸ† Awards & Patents

Principal investigator of 10+ funded projects including Jiangsu Provincial Natural Science and Wuxi β€œLight of Taihu Lake” programs.

Holder of 20+ patents, including β€œA trajectory tracking method for non-repetitive time-varying systems”.

Recognized with support from national initiatives such as the β€œ111 Plan”.

πŸ“š Notable Publications

πŸ†• 2025

Output feedback based PD-type iterative learning fault-tolerant control for uncertain discrete systems with actuator faults
πŸ“˜ Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
πŸ”— DOI: 10.1177/09596518241263003
πŸ‘₯ Yanxia Shen, Wei Zou, Lei Wang

πŸ”¬ 2024

An innovative dynamic observer for nonlinear interconnected systems with uncertainties
πŸ“˜ Transactions of the Institute of Measurement and Control
πŸ—“ Published: 2024-10-23
πŸ”— DOI: 10.1177/01423312241274007
πŸ‘₯ Nan Ji, Lei Wang, Xinggang Yan, Dezhi Xu

Iterative learning control with parameter estimation for non-repetitive time-varying systems
πŸ“˜ Journal of the Franklin Institute
πŸ—“ Published: 2024-02
πŸ”— DOI: 10.1016/j.jfranklin.2024.01.011
πŸ‘₯ Lei Wang, Ziwei Huangfu, Ruiwen Li, Xiewen (Sitman) Wen, Yuan Sun, Yiyang Chen

πŸ“Š 2023

Design of robust fuzzy iterative learning control for nonlinear batch processes
πŸ“˜ Mathematical Biosciences and Engineering
πŸ”— DOI: 10.3934/mbe.2023897
πŸ‘₯ Wei Zou, Yanxia Shen, Lei Wang

A Soft Actor-Critic Approach for a Blind Walking Hexapod Robot with Obstacle Avoidance
πŸ“˜ Actuators
πŸ—“ Published: 2023-10-21
πŸ”— DOI: 10.3390/act12100393
πŸ‘₯ Lei Wang, Li Ruiwen, Ziwei Huangfu, Yishan Feng, Yiyang Chen

Fully Distributed, Event-Triggered Containment Control of Multi-Agent Systems
πŸ“˜ Applied Sciences
πŸ—“ Published: 2023-10-07
πŸ”— DOI: 10.3390/app131911039
πŸ‘₯ Lei Wang, Guanwen Chen, Tai Li, Ruitian Yang

Slowness or Autocorrelation? A serial correlation feature analysis method
πŸ“˜ Journal of Process Control
πŸ—“ Published: 2023-01
πŸ”— DOI: 10.1016/j.jprocont.2022.11.010
πŸ‘₯ Qinghua Li, Zhonggai Zhao, Lei Wang

Mr. Jin QilinΒ  | Computer vision | Best Researcher Award

Mr. Jin QilinΒ  | Computer vision | Best Researcher Award

Hohai University, China.

Qilin Jin is a passionate researcher specializing in the application of artificial intelligence and software engineering. With a focus on integrating AI with real-world engineering challenges, he has made significant strides in areas such as sonar image analysis, defect detection, and structural monitoring. His innovative work has been recognized through impactful publications and contributions to the scientific community.

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πŸŽ“ Education

Qilin Jin is currently pursuing a Ph.D. in Computer Science, specializing in the applications of artificial intelligence and software engineering to solve complex real-world problems. His doctoral research focuses on leveraging advanced AI algorithms for defect detection and structural analysis. He holds a Master's Degree in Engineering, where his studies centered on intelligent systems and structural monitoring, providing a strong foundation for his innovative contributions to these fields.

πŸ’Ό Experience

Qilin Jin is an accomplished researcher with extensive experience in developing AI-driven solutions tailored for industrial and engineering applications. His work focuses on creating innovative methods for defect detection and segmentation, leveraging cutting-edge artificial intelligence technologies to enhance accuracy and efficiency. As a dedicated collaborator, Qilin actively contributes to multidisciplinary projects, combining expertise from various domains to address complex challenges in structural monitoring and intelligent systems.

πŸ” Research Interests

Artificial Intelligence Applications: Advanced algorithms for defect detection and structural analysis.

Software Engineering: Innovative methods to enhance engineering software development.

Deep Learning: Leveraging deep neural networks for real-time segmentation and detection tasks.

πŸ† Awards and Recognitions

Young Innovator Award for contributions to AI-based defect detection in sonar imaging.

Recognized for excellence in research by leading journals like Applied Sciences and Journal of Sound and Vibration.

πŸ–‹οΈ Publications

  1. Jin, Qilin, Han Qingbang, Qian Jianhua, et al. "Drainage Pipeline Multi-Defect Segmentation Assisted by Multiple Attention for Sonar Images," Applied Sciences, 2025, 15(2): 597.
    Cited by 5 articles.
  2. Jin Qilin, Han QingBang, Su NaNa, et al. "A deep learning and morphological method for concrete cracks detection," Journal of Circuits, Systems, and Computers, 2023, 4.
    Cited by 3 articles.
  3. Wu Yang, Han QingBang, Jin Qilin, et al. "LCA-YOLOv8-Seg: An Improved Lightweight YOLOv8-Seg for Real-Time Pixel-Level Crack Detection of Dams and Bridges," Applied Sciences, 2023, 13: 10583.
    Cited by 7 articles.
  4. Han YuFeng, Han QingBang, Zhang ShiGong, Su NaNa, Jin Qilin, Shan MingLei. "Semianalytical numerical iterative analysis for a one-dimensional second harmonic wave," Journal of Sound and Vibration, 2022, 8.
    Cited by 2 articles.