I am currently serving as a senior robotics engineer, leading the development of control systems for bio-inspired robots at NHY. I have a Ph.D. degree in mechanical and electrical engineering. My postdoctoral experience in wearables for movement biomechanics, coupled with a robust background in biomechanics, embedded programming, machine learning, wearable Inertial Measurement Units (IMUs), and bio-inspired robotics, positions me as a versatile professional.During my postdoctoral tenure at Shanghai Jiao Tong University's Wearable Systems Laboratory under the supervision of Prof. Peter Shull, I focused on investigating human biomechanics in landing tasks. This involved utilizing wearable sensors (IMUs) and machine learning techniques. In my doctoral research, I delved into the realm of adaptive neural control, exploring central pattern generators, reflex chains, sensory feedback, and learning mechanisms. The developed control algorithm not only facilitates the autonomous generation of adaptive self-organized locomotion in legged robots, such as quadruped robots but also enhances our understanding of animals' biological neural mechanisms. Additionally, my research aimed to create a generic adaptive neural controller applicable to various legged robots with diverse morphologies.I have honed my skills in Machine Learning, Wearable IMU Applications, biomechanics, adaptive neural control, and robotics. proficient in a range of development tools, I am adept at using PyTorch, TensorFlow, Robot Operating System (ROS), Python, C/C++, Linux, Siemens NX, CoppeliaSim, ADAMS, LpzRobot, and STM32.