Otavio Medeiros Feitosa currently works at the REgional Models and geo-Hydrological Impacts (REMHI) division at CMCC, where he develops machine learning models to support physical models and solve dynamic atmospheric problems. His expertise spans data assimilation, numerical modeling, and application of advanced AI techniques in meteorology, with a particular focus on precipitation nowcasting and convection-permitting models. At CMCC, he contributes to the development of high-resolution regional climate models and implements innovative approaches using artificial intelligence to enhance the understanding of localized atmospheric phenomena.

While working at CMCC, Feitosa is simultaneously pursuing his PhD in Meteorology at the National Institute for Space Research (INPE) in Brazil, where his research focuses on S2S prediction models using spherical convolutional neural networks. His academic background includes a Master’s degree in Meteorology from INPE and a Bachelor’s from Federal University of Pelotas, complemented by professional experience as a Researcher in Atmospheric Modeling at CEMPA and as a Data Scientist at Semantix. He has published papers on radar data assimilation, precipitation forecasting, atmospheric numerical simulations, and applications of deep learning in meteorology.