Wenhua Zhao

Wenhua Zhao is an Associate Professor at The University of Queensland and a globally recognized expert in offshore hydrodynamics and renewable energy technologies. He is the recipient of the prestigious ARC Future Fellowship (2024-2028) and DECRA Fellowship (2019-2022), with over 110 publications and six awards influencing both industry and academia. He has helped secure over AUD30 million research funding from both Australian Research Council and industry, contributing to transformative engineering practices in renewable energy sectors and oil & gas industry. His research focuses on Clean Energy, AI, and Climate Change, with groundbreaking studies on wave-structure interactions -- showcased by his multiple publications in Journal of Fluid Mechanics and industry-focused applications, a rare integration of theoretical research with practical implementation. He pioneers innovations in floating wind energy, floating solar, offshore aquaculture, and green hydrogen, leveraging artificial intelligence to transform offshore renewable energies. Wenhua has been a Deputy Editor for Ocean Engineering (No. 1 in marine engineering, ISI web), Associate Editor for the renowned ASME's Journal of OMAE, and editorial board member for the Q1 journal Applied Ocean Research. His teaching, particularly the "Design of Offshore Energy Systems" course, has prepared hundreds of students for impactful careers in coastal and ocean engineering. Civil engineering, Engineering, Fluid mechanics and thermal engineering, Hydrodynamics and hydraulic engineering, Marine engineering, Maritime engineering, Maritime engineering not elsewhere classified, Naval architecture, Ocean engineering, Resources engineering and extractive metallurgy, Resources engineering and extractive metallurgy not elsewhere classified, Ship and platform structures (incl. maritime hydrodynamics), Structural dynamics, Structural engineering

[2026] Modelling linearly excited resonant heave response of a semi-submersible floating wind turbine. Liu, Lulu, Zhao, Wenhua, Milne, Ian A. and Wolgamot, Hugh A. (2026). Modelling linearly excited resonant heave response of a semi-submersible floating wind turbine. Ocean Engineering, 362 (P2) 126333, 126333-126333. doi: 10.1016/j.oceaneng.2026.126333 [2026] Attention-based machine learning for short-term motion prediction of a floating offshore wind turbine. Chen, Jialun, Gunawan, David, Taylor, Paul H., McCauley, Guy and Zhao, Wenhua (2026). Attention-based machine learning for short-term motion prediction of a floating offshore wind turbine. Ocean Engineering, 358 (Part 3) 125780, 1-11. doi: 10.1016/j.oceaneng.2026.125780 [2026] Wave power absorption of semi-circular oscillating water