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University of Cambridge > Talks.cam > Energy and Environment Group, Department of CST > NERC Facilities for AI and Earth Observation: Project examples, Directions and Geospatial Foundation Models
NERC Facilities for AI and Earth Observation: Project examples, Directions and Geospatial Foundation ModelsAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact lyr24. Bio Dr David Moffat is the AI Data Science Lead at Plymouth Marine Laboratory, where he bridges computer science and environmental research to advance our understanding of marine ecosystems through artificial intelligence. His work focuses on developing geospatial foundation models, Earth observation systems, and computer vision techniques to monitor ocean health and biodiversity. David leads several high-impact initiatives at the intersection of AI and marine science. As PML lead for Granite-Geospatial-Ocean Foundation Model developed with IBM Research, STFC Hartree Centre, and the University of Exeter—he has created a pioneering foundation model that analyses Sentinel-3 satellite imagery to map phytoplankton distributions and net primary production. Openly released to support global collaboration, this work improves estimates of ocean carbon absorption, a key uncertainty in climate modelling. His research portfolio includes underwater benthic species detection using advanced computer vision (supported by the Bezos Earth Fund), harmful algal bloom detection, and coastal ecosystem monitoring. David’s technical expertise spans deep learning, signal processing, and time series analysis, with particular strength in adapting AI methodologies for complex environmental datasets. David has delivered machine learning and Earth observation training to over 500 participants across academic, governmental, and international organisations, helping build capacity in AI-driven environmental science. He holds a BSc in Artificial Intelligence and Computer Science from the University of Edinburgh, an MSc in Signal Processing, and a PhD in Computer Science from Queen Mary University of London. His interdisciplinary background in audio signal processing and intelligent systems provides a unique foundation for tackling the computational challenges of marine and environmental monitoring. He has authored over 30 peer-reviewed publications and book chapters. This talk is part of the Energy and Environment Group, Department of CST series. This talk is included in these lists:
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