My research interests are in the intersection of machine learning and Earth sciences. I have developed machine learning models for Earth observation with satellite images and for weather and energy forecasting. In 2020, I participated in the NASA Frontier Development Lab research sprint working on monitoring water on small streams. In 2019, I also participated in the Frontier Development Lab 2019 Europe research sprint working with the Disaster Prevention, Progress and Response team on onboard flood segmentation. During 2017 I worked under a Google Earth Engine Award project developing machine learning cloud detection algorithms (some results). Previously I worked in renewable energy forecasting at MeteoLogica.
My research involves convolutional neural networks for semantic segmentation, transfer learning and uncertainty estimation in deep learning applied to water and cloud detection.
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