Victoria Foing is a data scientist based in London with 8 years of professional experience and 5+ years focused on machine learning and remote sensing for environmental impact. She has built and operationalized geospatial AI pipelines using optical, SAR, and LiDAR data to monitor forests and map biomass, work that fed into climate-impact products and was presented at IGARSS 2024. At Sylvera she progressed from intern to senior engineer, increasing coverage and accuracy of forest-tracking models, and now applies that domain expertise to methane monitoring and analytics at GHGSAT. Her background spans astronomy (ML for exoplanet transit analysis at ESA) to healthcare and neuroscience projects, reflecting a strong interdisciplinary approach to real-world ML problems. Victoria combines production-grade engineering with research communication, bridging novel modeling techniques and operational deployment in climate and space domains.
8 years of coding experience
6 years of employment as a software developer
High School International Baccalaureate, High School International Baccalaureate at American School of the Hague
Master of Science - MSc Artificial Intelligence, Master of Science - MSc Artificial Intelligence at University of Amsterdam
Bachelor’s Degree Major Concentrations Computer Science & Geography (Urban Systems) Minor in Environment, Bachelor’s Degree Major Concentrations Computer Science & Geography (Urban Systems) Minor in Environment at McGill University
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