The ocean covers 70.8% of the Earth’s surface: a vast space that is still poorly understood. The aim of Perrine’s thesis is to combine different types of ocean observation data (satellite images, buoys, boats, etc.) and use artificial intelligence to gain a better understanding of the underlying physical phenomena.
Her work involves adapting algorithms to model ocean currents based on these observations, in particular using neural networks.
She then uses the physical laws established in oceanography to verify that the reconstruction of the currents is accurate, and even improved.
Having long been drawn to the world of research and ocean observation, Perrine decided to combine these two passions. After obtaining an engineering degree in hydrography and oceanography, she began training (at the beginning of her thesis) in artificial intelligence techniques. These are complementary skills that she enjoys sharing with the engineering students under her supervision.
Watch other interviews with PhD students on the ENSTA Bretagne’s YouTube channel.
news
