About Me

I am a Senior Research Scientist at Google Research in San Francisco, where my work focuses on artificial intelligence for weather forecasting, climate modeling, and environmental risk assessment. Recently, my research has centered on probabilistic generative modeling for ensemble prediction and regional risk (Nature Machine Intelligence, cover; PNAS; Science Advances), as well as agentic AI systems for operational environmental forecasting (arXiv).

More broadly, I am interested in developing methods that accelerate scientific discovery using AI, from autonomous research workflows that formulate, test, and refine quantitative models to probabilistic and physics-informed machine learning for complex dynamical systems. Weather, climate, and environmental processes offer a rigorous proving ground for these methods, demanding calibrated uncertainty, fidelity to physical laws, and accurate prediction of rare extremes. At the same time, advances in these areas carry immediate societal impact across energy systems, water management, agriculture, and resilient infrastructure. My research has been featured in Science, Bloomberg, and the PNAS podcast.

I earned my PhD at the California Institute of Technology, where I worked with Tapio Schneider on atmospheric turbulence, convection, and data-driven climate modeling. Prior to Caltech, I received Bachelor’s and Master’s degrees in Aerospace Engineering at Universidad Politécnica de Madrid (Spain) and ISAE-SUPAERO (France), respectively.