RS Machine Learning Engineer
Dr. Fernando Paolo develops machine learning algorithms for global analysis of satellite data to investigate human activity at sea and associated environmental change. Fernando is currently working on an AI-powered object detection system for Global Fishing Watch using petabytes of synthetic aperture radar imagery and cloud computing, with the goal of revealing non-broadcasting vessels and monitoring offshore infrastructure around the world.
Before joining Global Fishing Watch, Fernando worked as a postdoctoral scholar at the NASA Jet Propulsion Laboratory, where he used radar and laser satellite measurements to quantify current ice sheet loss and global sea level change. In 2015, he received the NASA Most Valuable Player Award for research in cryospheric sciences. Fernando obtained his doctorate in geophysics from the University of California, San Diego, and has authored numerous articles on climate research using statistical/ML methods. He has also participated in several scientific cruises to the Southern Ocean, including an expedition to Antarctica. Fernando is a strong advocate of open source and open data.