Jhayron S. Pérez-Carrasquilla

Jhayron joined the University of Chicago Data Science Institute as an AI for Climate Postdoctoral Scholar in 2026. He develops and applies AI methods for Earth system prediction, with a particular focus on improving subseasonal-to-seasonal (S2S) forecasts of extreme events and understanding their physical sources of predictability. He received his PhD in Atmospheric and Oceanic Science from the University of Maryland, where his research examined predictability across timescales, large-scale circulation, tropical variability, and extreme events. His work combines Earth system models, reanalyses, observations, and data-driven methods, including deep learning, explainable AI, and causal discovery. He was previously an ASP Graduate Visitor at NSF NCAR and contributes to initiatives at the intersection of climate science and AI, including WCRP Fresh Eyes on CMIP and the AMS Committee on AI Applications to Environmental Science. Outside of research, he enjoys soccer, music, movies, and reading.