Daniel Precioso is a data scientist who applies machine learning techniques to solve real-world problems in diverse industries. With a background in physics and data science, he has made valuable contributions to successful projects like UCAnFly, where he worked on designing a nanosatellite for testing emerging technologies in space-based gravitational wave detectors.

During his PhD at Cádiz University, Daniel and his team “Caleta” developed a computer vision-based contactless monitoring system for newborns, named NeoCam. They presented their project to the OpenCV AI Competition 2021, along with over 1,400 other computer vision solutions from researchers and institutions all over the world. They won second place at the world final.

Daniel’s current research interests are centred around the Blue Economy, which focuses on the sustainable use of ocean resources for economic growth. He has conducted research on sustainable fishing by studying the behaviour of tuna schools using data science and machine learning. Nowadays, Daniel’s focus is on weather routing, which involves optimising marine shipping routes using real-time ocean current, wind, and wave data. His weather routing research began during Ocean Hackathon 2021, when his team’s solution won 2nd place. Daniel also completed a research internship at Dalhousie University, following his research on the Blue Economy.