About me
Originally from Colombia, I'm currently a Ph.D. candidate studying atmospheric predictability and climate dynamics by leveraging machine learning techniques. I work with Dr. Maria Molina at the PARETO Group. Currently, I am part of the Fresh Eyes on CMIP initiative, working with the Data Analysis group, focusing on multi-model ensembles. I am also part of the American Meteorological Society's Committee on Artificial Intelligence Applications to Environmental Science. Additionally, I recently visited NCAR in Boulder, Colorado, as part of the Graduate Visitor Program. I focused on evaluating long-term changes in the large-scale mid-latitude circulation and the impacts on surface weather.
My main research interests are large-scale Earth system dynamics, variability, and predictability, extreme weather events, and climate change. My work has mainly aimed at applying machine learning and numerical modeling to gain a deeper understanding of processes in climate, meteorology, hydrology, and air quality.
Research interests
I'm currently deepening my knowledge of Earth system dynamics and machine learning. More specifically, I use recently developed computational and data-driven methods to better understand the processes that modulate the occurrence and characteristics of mid-latitude large-scale weather regimes. These large-scale features affect people's everyday lives by driving the occurrence of extreme weather events under different climate variability change scenarios. Some methods I use in my research include tree-based machine learning, deep learning, eXplainable AI, data-driven causal discovery, and unsupervised clustering. I combine these tools with Earth system reanalyses and models to unveil Earth system drivers of subseasonal-to-seasonal predictability and the effects of climate variability and change. I look forward to continue exploring these same topics in the future.
My master's thesis was mainly about how the internal dynamics of tropical cyclones behave when the storm is intensifying, and my undergraduate thesis was about how the origin of air parcels affected the characteristics of extreme precipitation events over the Colombian Andean region. Additionally, I have some experience with idealized modeling and empirical forecasts of air quality, meteorological, and hydrological variables. I have mostly used Python during my career to handle data from satellite, reanalysis, ground-based stations, radar, and model outputs.