Experience
Associate Professor
Assistant Professor
Postdoctoral research fellow
Researcher
Education
PhD in Marine Technology
Department of Marine Technology, Norwegian University of Science and Technology, Trondheim, NorwayMSc in Marine Cybernetics
Department of Marine Technology, Norwegian University of Science and Technology, Trondheim, NorwayBEng in Ocean Engineering
Department of Ocean Engineering, Dalian University of Technology, China
Environment Perception and Situation Awareness
Traditional response prediction methods rely on historical data, but due to the sparsity of time series data, they often lead to insufficient prediction accuracy and limited reliability. To break through this bottleneck, my research is committed to developing environmental stereo in-situ perception methods based on advanced sensing technologies such as multi-camera vision, lidar, and fiber Bragg grating. Combining theories of multi-body dynamics, hydrodynamics, and aerodynamics, and introducing computer vision and system identification technologies, high-precision prediction of environmental loads and operational situations at multiple time scales is achieved. This research aims to provide data support and key technological breakthroughs for marine operations with high real-time requirements.
Intelligent Decision Support for Marine Operations
Currently, high-demand marine operations still heavily rely on manual experience, with limitations such as strong subjectivity, low efficiency, and high risks. To ensure operational safety, conservative time windows are often adopted, resulting in shortened effective operation periods and increased costs. To address these challenges, my research focuses on the development of intelligent decision support theories: by introducing artificial intelligence algorithms such as computer vision, optimization theory, and deep learning, combined with technologies such as digital twins and large-scale preview models, dynamic deduction and risk pre-identification of operation processes are carried out, thereby enhancing the operational prediction capabilities and decision intelligence level in complex marine environments.
Automatic Control of Onboard Equipment and Marine Robotics
To improve the efficiency of operation equipment, research and development of general and new marine engineering equipment, including but not limited to dynamic positioning systems, thruster-assisted position mooring systems, unmanned ships, unmanned aerial vehicles, underwater robots, robotic arms, lifting systems, flexible cable-driven parallel systems, heave compensation systems, anti-rolling tanks, quadruped robots, etc., and further research and implement their guidance, navigation, and nonlinear control strategies for multi-moving bodies in marine environments. By integrating intelligent algorithms with dynamic feedforward control, the system response speed and robustness are enhanced.
