Tianning Tang

Tianning Tang is a Lecturer in Fluid Mechanics at the University of Manchester, Department of Mechanical Engineering. His research focuses on extreme events in fluid mechanics, particularly using machine learning to predict extreme waves and structural loading, with an emphasis on nonlinear wave dynamics and instabilities. He joined the University of Manchester in 2025 and has previously worked as a Course Director of the Intelligent Earth CDT programme and as an Eric and Wendy Schmidt AI in Science Postdoctoral Fellow at the University of Oxford. His work has been featured in BBC Science Focus, and he collaborates with researchers globally, including at the University of Oxford. He supervises PhD and MSc students and is actively seeking fully funded PhD candidates.

Tim (Tianning) Tang is a researcher in Ocean Engineering with a focus on Rogue wave dynamics, Machine Learning, and Knowledge Discovery. His work explores the statistical and physical characteristics of extreme ocean waves, including rogue waves, through experimental and numerical studies. Tang applies Machine Learning techniques to predict wave behavior and improve the understanding of nonlinear wave interactions. His research also involves the development of models for wave loads on offshore structures and the analysis of wave data from field measurements. Tang's contributions span both theoretical and applied aspects of ocean engineering, with an emphasis on enhancing predictive capabilities and data-driven insights.