Artificial Intelligence to Uncover Fish Responses to Disturbed Flows

Artificial Intelligence to Uncover Fish Responses to Disturbed Flows

The mechanisms of aquatic animal swimming become a central issue for researchers and engineers who wish to develop underwater robotics with superior locomotion capability. Aquatic animals suspended in water are subject to the complex nature of three-dimensional flows, which have the potential to perturb the swimming motions of the animals. One of the most fascinating yet least understood attributes of aquatic animals is their ability to rapidly adapt their motions to complex flows and environment changes. In this project, we would like to apply/extend AI to uncover fish fast gait transitions and fish responses to disturbed flows, and to discuss the associated flow physics.

Scholarships: 
International Postgraduate Research Scholarships
Supervisor: 
Dr Fangbao Tian
Associate Professor John Young