Andrianirina Rakotoharisoa

Visiting Researcher

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I am a 3^rd-year PhD candidate in Machine Learning at Imperial College London, based in the Department of Earth Science & Engineering. My research focuses on the “Coupling of Remote Sensing Data and Machine Learning for Greenhouse Gas Emissions Monitoring” and specifically explores generative models (diffusion models), super-resolution, and the analysis of spatio-temporal data for climate applications. Within this context, the collaboration with the European Space Agency (ESA) will investigate the implementation of an “AI-driven, global, near real-time, active fire detection method using remote sensing data”.  The project will aim to improve the accuracy and timeliness of wildfire detection using deep learning techniques explored in the first chapters of my PhD. Prior to my PhD, I obtained a master’s degree in engineering from the Ecole Centrale de Nantes and specialized in Applied Mathematics and Computer Science. When I’m not working, I enjoy running, swimming and discovering new places and people.

Research Activities

Over the 3-month period, the main research areas of the placement will be:

1. Designing and training a super-resolution deep learning model to downscale data from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard Sentinel-3, using historical data to train the model.
2. Performing anomaly detection with a diffusion model on the downscaled data to identify active fire pixels and newly burnt areas, while also integrating auxiliary physical variables (e.g., vegetation, wind) to ensure that the model’s outputs are physically consistent.