Prof. Wei Ma | Robotics and Automation | Research Excellence Award

Prof. Wei Ma | Robotics and Automation | Research Excellence Award

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.

Dr. Daxiong Ji | Robotics | Research Excellence Award

Dr. Daxiong Ji | Robotics | Research Excellence Award

Associate. Professor | Zhejiang University | China

Dr. Daxiong Ji is a distinguished researcher whose extensive contributions in marine science and intelligent systems are firmly rooted in robotics, with his work consistently advancing the global understanding of autonomous systems. His professional journey demonstrates a sustained commitment to robotics, especially in marine robotics, underwater robotics, intelligent robotics, and control-oriented robotics applications. As an associate professor and doctoral supervisor at the Ocean College of Zhejiang University, he has established a strong research portfolio that reflects a deep engagement with cutting-edge robotics innovations. His scholarly output exceeds forty peer-reviewed publications and more than twenty invention patents, each reinforcing his influence in the evolution of advanced robotics for underwater environments. His collaborations with leading experts, including international partnerships in control theory and underwater systems engineering, highlight his role in strengthening interdisciplinary ties across global robotics communities. Dr. Daxiong Ji’s research in marine robotics has driven novel solutions in dynamic modeling, autonomous navigation, fault diagnosis, and intelligent perception systems. His pioneering development of underwater multi-rotor platforms and data-driven diagnostic systems for deep-sea thrusters showcases high-impact applications of robotics that enhance safety, operational reliability, and environmental sustainability. His inventive work on intelligent robotic platforms for ship maintenance demonstrates the societal value of robotics, particularly in reducing labor intensity, improving maritime efficiency, and contributing to ocean-engineering innovation. Beyond research, he serves the international robotics field as an IEEE senior member, guest editor, reviewer for numerous prestigious journals, and evaluator for major scientific programs, further solidifying his leadership within the broader robotics landscape. His academic service and accomplishments reflect a holistic dedication to advancing robotics technologies while nurturing the next generation of scientists in marine robotics and intelligent systems. Google Scholar profile of 1211 Citations, 16 h-index, 22 i10-index.

Profiles: Google Scholar | ORCID

Featured Publications

1. Zhang, B., Ji, D., Liu, S., Zhu, X., & Xu, W. (2023). Autonomous underwater vehicle navigation: A review. Ocean Engineering, 273, 113861.

2. Gan, W., Zhu, D., & Ji, D. (2018). QPSO-model predictive control-based approach to dynamic trajectory tracking control for unmanned underwater vehicles. Ocean Engineering, 158, 208–220.

3. Bi, Z., Zhang, N., Xue, Y., Ou, Y., Ji, D., Zheng, G., & Chen, H. (2024). Oceangpt: A large language model for ocean science tasks. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics.

4. Chen, C. W., Jiang, Y., Huang, H. C., Ji, D. X., Sun, G. Q., Yu, Z., & Chen, Y. (2017). Computational fluid dynamics study of the motion stability of an autonomous underwater helicopter. Ocean Engineering, 143, 227–239.

5. Ji, D., Yao, X., Li, S., Tang, Y., & Tian, Y. (2021). Model-free fault diagnosis for autonomous underwater vehicles using sequence convolutional neural network. Ocean Engineering, 232, 108874.