Summary
Ryan Lagerquist is a Principal Atmospheric Scientist and research meteorologist who has spent over a decade pioneering ML/AI solutions for weather and climate, with eight years of focused research experience and recent leadership roles at CIRA/NOAA and MyRadar. He blends deep domain expertise—tropical cyclones, severe weather, wildfire, radiative transfer, and remote sensing—with practical ML skills in Python and MATLAB to build emulators, uncertainty-aware post-processing, and multi-lead forecasting systems. Ryan has led funded projects exceeding $2.6M, served as PI on a $2M task, and shepherded ML integration into operational workflows like HRRR emulation and GeoCenter center-fixing pipelines. His work advances explainable AI and uncertainty quantification in atmospheric science, and he’s notable for creating scale-aware loss functions and neural radiative-transfer emulators used to accelerate NWP. Based in Boulder, he also has deep mentoring and teaching experience, having designed short courses and supervised multiple researchers while producing reproducible code and public data archives.
9 years of coding experience
12 years of employment as a software developer
Bachelor of Science - BS, Atmospheric Sciences and Meteorology, 3.94 GPA, Bachelor of Science - BS, Atmospheric Sciences and Meteorology, 3.94 GPA at University of Alberta
Doctor of Philosophy - PhD, Meteorology, Doctor of Philosophy - PhD, Meteorology at University of Oklahoma
English, French