Hugo Lee is a data scientist at NASA JPL with 11 years of experience bridging atmospheric science and statistical modeling, now serving as principal investigator on a NASA CMAC project and chairing the Apache Open Climate Workbench effort. He holds a Ph.D. in Atmospheric Sciences from UIUC and draws on deep expertise in stratospheric dynamics, atmospheric chemistry, air quality modeling, and neural-network-based satellite retrievals. At JPL he develops and leads RCMES to evaluate climate models against satellite observations, turning complex observational streams into robust evaluation metrics. His background in quantile regression and probability-density comparisons informs novel diagnostic tools that make model biases interpretable and actionable. Fluent in scientific programming across Fortran, IDL, and R, he brings a rare combination of operational code development (e.g., typhoon-tracking software) and advanced statistical method development.
11 years of coding experience
7 years of employment as a software developer
BS, Atmospheric Sciences, BS, Atmospheric Sciences at Seoul National University
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