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Rocío Joo is a data scientist on the research and innovation team at Global Fishing Watch, where she leads research in Latin America, coordinating with partners throughout the region.

With her scientific background and experience in statistical programming and movement analysis, she contributes to team projects and scientific papers, particularly those related to fishing vessels and seabirds. Her main focus is the forced labor risk project, where she develops a machine learning algorithm that uses forced labor reports and fishing vessels data to predict if vessels have a high or low risk of forced labor based on their movement patterns and characteristics. Rocío is an enthusiastic member of the Global Fishing Watch Diversity, Equity, and Inclusion Committee, and is passionate about data ethics, responsible machine learning and good programming practices.

Prior to Global Fishing Watch, Rocío followed an academic path. She obtained her bachelor’s degree in statistics engineering at Universidad Nacional de Ingeniería in Peru, her master’s degree in biostatistics and her doctorate in ecosystems at Université de Montpellier, France. She then worked at Instituto del Mar del Perú, Institut Français de Recherche pour l’Exploitation de la Mer, France, and the University of Florida, U.S., conducting fisheries and movement ecology research. Rocío is a happy and active member of the global R programming community. When she is away from her work computer, she spends most of her time improving her drumming skills, playing cajón or other percussion instruments, trying to teach herself to play piano, reading history books, or cycling towards the sea.