About

Hi, I’m Lewis. My background is in statistics, machine learning, and optimization.

I apply this to my work as a Computational Scientist in the Division For Climate Modeling and Air Pollution at the Norwegian Meterological Institute in Oslo. Here I work on climate and air pollution model evaluation and uncertainity quantification. I contribute to the Python package pyaerocom, which offers a powerful and flexible framework for comparing models against observations and is used extensively throughout our projects. I additionally manage and contribute to contracts for the European CAMS project and CAMEO.

I completed my PhD in Statistics from the Department of Applied Mathematics and Statistics at Colorado School of Mines in December 2021. My thesis developed computational and theoretical tools for analyzing massive nonstationary spatial data sets. A primary component of my PhD was as a Research Assistant at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. There I developed and released scalable machine learning models which allow users to compute with hundreds-of-millions of observations and reduced computation times by 75%.

Prior to that, I completed my undergraduate studies concentrating in mathematics, computer science, and agriculture at Hampshire College in Amherst, Massachusetts.