My research focuses on understanding how clouds and precipitation form in different environments. I am interested in convective events and what drives them to become extremes. In my work, I mainly use remote sensing observations from active and passive sensors deployed on different platforms. To analyze the data and extract the most information out of it, I exploit deep learning methods that have been developed for computer vision and threat images and videos. The most important goals of my research are, on one hand, to better understand microphysical processes from observations. Beyond this, I want to exploit observations to improve numerical weather prediction models and reduce the biases in precipitation and cloud forecasts. My research is strongly interdisciplinary because the observations and the methods I use can have a lot of different applications, from nowcasting to renewable energy forecasts.