Associate Professor | Tianjin University | China
Prof. Wei Ma is a distinguished researcher recognized for significant contributions to underwater glider development within the domain of Robotics and Automation, where Robotics and Automation remain central to his scientific endeavors. As an Associate Professor at Tianjin University, Prof. Wei Ma has advanced Robotics and Automation through intelligent operation, hydrodynamic modelling and control of unmanned marine platforms. His research encompasses the optimization of underwater glider mechanics, variational mode decomposition for marine data processing and model based multi objective control, each contributing to a growing impact on Robotics and Automation applied to ocean engineering. With a record of ten indexed publications and fifteen patents published or under processing, Prof. Wei Ma continues to demonstrate excellence in Robotics and Automation research with high quality outputs featured in reputable journals including Physics of Fluids, Chaos, Ocean Engineering, Journal of Marine Science and Engineering and Journal of Mechanical Engineering Science. His work on air droppable underwater glider water entry, virtual prototype modelling and shape memory alloy based buoyancy systems remains widely noted in Robotics and Automation due to innovative approaches to control, sensing, networking technologies and AI driven data analytics. Prof. Wei Ma further supports the Robotics and Automation community as a reviewer for respected journals, reflecting recognition of his scholarly authority and scientific judgement. His achievements include major technology progress recognition for water surface glider engineering and an outstanding contribution award for glider system product deployment, strengthening the relevance of Robotics and Automation to maritime applications and marine intelligence systems. Through ongoing projects, expanding research themes and growing publication strength, Prof. Wei Ma continues to shape Robotics and Automation innovation with strong societal and technological relevance. Scopus profile of 231 Citations, 35 Documents, 8 h-index.
Profiles: Scopus | ORCID
Featured Publications
1. Yang, P., Wang, Y., Ma, W., Niu, W., Song, Y., & Li, Q. (2025). Fused spatial–temporal graph convolutional networks for ocean currents forecasting using underwater glider measurements. IEEE Journal of Oceanic Engineering.
2. Xi, H., Ma, W., Song, Y., Fa, S., Song, J., & Yang, M. (2025). Energy consumption prediction and endurance optimization for underwater gliders based on data-model fusion. Engineering Applications of Artificial Intelligence.
3. Lyu, G., Wu, S., Song, J., Fa, S., Wang, W., Miao, Z., Gong, F., Ma, W., & Wang, C. (2025). Model and data-driven hydrodynamic identification and prediction for underwater gliders. Physics of Fluids.
4. Ma, W., Wang, Y., Wang, S., Li, G., & Yang, S. (2019). Optimization of hydrodynamic parameters for underwater glider based on the electromagnetic velocity sensor. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.