Dr. Caizhi Li | Industrial | Industry Innovator Award
Doctorate at Air Force Engineering University, China
Profiles
Summary
Dr. Caizhi Li is a dedicated researcher in aeronautical and astronautical sciences, specializing in aerospace composites, wave-absorbing materials, and artificial intelligence applications. With a strong foundation in electrical engineering, aeronautical engineering, and cutting-edge non-destructive testing methods, Dr. Li has contributed significantly to advanced damage detection and intelligent recognition technologies.
Education
- PhD in Aeronautical and Astronautical Sciences and Technology
Air Force Engineering University (2022.03–Present) - Master’s in Aeronautical Engineering
Air Force Engineering University (2019.09–2022.01) - Bachelor’s in Electrical Engineering and Automation
Air Force Engineering University (2015.09–2019.06)
Professional Experience
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- Foundation of National Major Science and Technology Projects of China (No. 2019-Ⅵ-0015-0130)
- National Science and Technology Major Project (J2019-III-0009-0053)
Research Interests
- Aerospace Composites & Wave-Absorbing Materials
- Damage mechanisms and detection.
- Non-Destructive Testing (NDT)
- Certified in Ultrasonic NDT (Level 2), Infrared NDT, and Weak Magnetic NDT.
- Artificial Intelligence
- Applications in object detection, image segmentation, and signal recognition.
Publications
TranSR-NeRF: Super-resolution neural radiance field for reconstruction and rendering of weak and repetitive texture of aviation damaged functional surface
- Authors: HU, Q., XU, H., WEI, X., HAN, X., LI, C.
- Journal: Chinese Journal of Aeronautics
- Year: 2024
Aeroengine Blades Damage Detection and Measurement Based on Multimodality Fusion Learning
- Authors: Wu, X., Wei, X., Xu, H., He, W., Zhou, L.
- Journal: IEEE Transactions on Instrumentation and Measurement
- Year: 2024
PointCNT: A One-Stage Point Cloud Registration Approach Based on Complex Network Theory
- Authors: Wu, X., Wei, X., Xu, H., Yin, Y., He, W.
- Journal: Remote Sensing
- Year: 2023
Study on intelligent and visualization method of ultrasonic testing of composite materials based on deep learning
- Authors: Hu, Q., Wei, X., Guo, H., He, W., Pei, B.
- Journal: Applied Acoustics
- Year: 2023
Study on the impact erosion wear resistance and damage evolution of TiN films under different impact cycles
- Authors: Wang, S., He, W., Zhang, H., Li, C., Zhang, Y.
- Journal: Thin Solid Films
- Year: 2023
Dr. Caizhi Li | Industrial | Industry Innovator Award