I was a Postdoctoral Research Associate with GeoHAI lab and the Department of Geography.
My research interests include developing machine learning algorithms for different geospatial and geoscience applications, ranging from the classification of thin sections and microfossils to the forecasting of space weather inside the Earth’s outer radiation belt. I also have experience with advanced image processing techniques for seismic attributes development, as well airborne gamma-spectrometric data analysis and other geophysical methods.
My research at GeoHAI funded by the National Science Foundation to develop novel deep (convolutional) neural networks for the harmonization of heterogenous datasets including multi-SAR (Synthetic Aperture Radar) images and other remotely sensed data for sea ice mapping. During my time at CU, I also received a grant from NASA to further advance this work.
Search for Rafael Pires de Lima's papers on the Publications page