About me¶
I'm a computational scientist at the NSF National Center for Atmospheric Research (NSF-NCAR) in Boulder, Colorado. My work lives at the intersection of atmospheric science, HPC, and AI/ML.
Currently serving as the Technical Lead of the NSF-NCAR Community AI Ecosystem initiative, I coordinate eight labs and 50+ stakeholders to build unified geospatial AI/ML infrastructure for Earth system science.
My background spans numerical weather prediction, distributed GPU training, performance optimization on HPC/Cloud architectures, and building scalable data workflows for large geospatial datasets. I'm passionate about open science and fostering community-driven computational geoscience.
I'm an active open-source contributor and technical leader in the Pangeo ecosystem, serving as a core contributor to Xarray, CuPy-Xarray, and Pythia. I enjoy teaching and have delivered tutorials at SciPy, ESDS, and NCAR on topics ranging from scalable geospatial data analysis to distributed AI/ML workflows.
I hold a Ph.D. in Chemical Engineering from the University of Iowa, where my research focused on atmospheric chemistry modeling, performance analysis, and optimization of weather and air quality models.