AS
Atmospheric Sciences

Makoto Kelp

Makoto Kelp is an Assistant Professor in the Department of Atmospheric Sciences and the Wilkes Center for Climate Science & Policy at the University of Utah. His research applies data science and ML/AI techniques to gain greater mechanistic insights into wildfire smoke mitigation, global modeling of atmospheric chemistry, and air pollution sensing strategies. He currently co-leads the Statistical Learning in Atmospheric Chemistry (SLAC) webinar group and co-chairs the Tropospheric Ozone Assessment Report (TOAR) Working Group on Machine Learning for Ozone (ML4O3).

Harnessing Machine Learning to Advance Tropospheric Ozone Science

and December 5, 2025
Harnessing Machine Learning to Advance Tropospheric Ozone Science

Machine learning (ML) and Artificial Intelligence (AI) offer powerful tools to address long-standing scientific challenges. At the molecular scale, we’ve seen projects like AlphaFold discover unknown protein structures and how they might interact with other molecules.  At the planetary scale, ML-driven models like GraphCast (Google), AIFS (ECMWF) and ACE (Allen Institute for AI) are revolutionizin ...[Read More]