Théo Archambault

From an early age, I have been deeply curious about science, initially drawn to paleontology and biodiversity, and later to mathematics and physics. My journey began with internships at natural history museums, followed by preparatory classes in mathematics and physics, and an engineering degree from a school in Grenoble. This path solidified my passion for natural sciences and led me to pursue a Ph.D., during which I developed deep learning algorithms to reconstruct critical ocean variables from spatial observations. I firmly believe that physics and deep learning can mutually enhance each other for the greater good.I rejoined Amphitrite’s team to transform this belief into practical solutions. My primary contribution in Amphitrite work involves designing, validating, and deploying state-of-the-art deep learning models to tackle complex oceanographic challenges, providing innovative solutions for shipping, environmental, and defense applications.