I am Juan Francisco Amieva, a researcher in Earth Observation and Artificial Intelligence, currently pursuing an industrial PhD in AI between Tracasa Instrumental and the Public University of Navarre (UPNA). My work focuses on deep learning for Synthetic Aperture Radar (SAR) image super-resolution, and as a Visiting Researcher at ESA Φ-lab, I contribute to the development of a foundational model for multi-frequency SAR to improve large-scale forest characterization.
I hold an M.Sc. in Geoinformatics Engineering (with honors) from Politecnico di Milano; a Master in Data Intelligence (Big Data orientation) from the National University of La Plata; a Specialization in Transport Policy and Planning from the National University of San Martín; and a degree in Industrial Engineering from the National University of La Plata.
Over the past three years, I have contributed to Tracasa Instrumental S.L., developing AI-driven solutions that combine satellite data analysis and geospatial intelligence for research and operational applications.
Currently, I serve as a Data Scientist in Earth Observation at Tracasa Instrumental (Spain), where I develop deep learning models for remote sensing applications, with a particular focus on SAR image enhancement techniques.
My expertise lies in the integration of Earth Observation and AI for satellite data analysis. I work with SAR, multispectral, and hyperspectral imagery, developing deep learning models for a wide range of applications, including chlorophyll-a estimation in lakes, crop yield prediction, density estimation, object detection, super-resolution, and change detection. This combination of AI and EO techniques allows me to design scalable and transferable models that extract meaningful information from complex satellite datasets. My work aligns closely with ESA Φ-lab CIN’s mission of fostering AI innovation in Earth Observation and advancing the development of next-generation geospatial models.
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