Department: Chemical Engineering
Advisor: Dan Schwartz
As the impact of climate change becomes increasingly clear, the need for sustainable energy production, storage, and materials has grown more pressing. To meet this need for improving implementation of novel and existing technologies, I have been leveraging modern data science methods with a broad range of uses. While my research has primarily been in the field of energy storage — developing tools to study electric transit vehicle energy use and aging — I have also worked on the development of machine learning for non-natural nucleotide sequencing. I anticipate continuing my intersectional work across a variety of disciplines, with the goal of exploring and advocating for improved sustainable materials and energy technology.