Summary
Raphael Attié is a research scientist and heliophysicist with 11 years of experience translating solar physics research into operational space-weather tools at NASA GSFC and partnering institutions. He specializes in machine learning, computer vision, and petabyte-scale image analytics applied to solar imagery from missions like SDO and STEREO, with a track record of characterizing flare and CME precursors to improve forecasts. His background spans academic PhD work in solar physics and image processing, international research posts, and hands-on software development in C/C# for telescope calibration and historical sunspot digitization. Comfortable moving models from research to operations, he blends deep domain expertise with data-science engineering to deploy scalable R2O solutions that directly support operational forecasting. An interesting non-obvious strength is his early experience building and benchmarking DIY drone sensors, reflecting a practical hardware-software curiosity that complements his large-data, algorithmic work.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Solar Physics and Image Processing, Doctor of Philosophy - PhD, Solar Physics and Image Processing at Max Planck Institute For Solar System Research
Doctor of Philosophy - PhD, Solar physics and Image processing, Magna Cum Laude, Doctor of Philosophy - PhD, Solar physics and Image processing, Magna Cum Laude at Technische Universität Carolo-Wilhelmina zu Braunschweig
English, French, German