
Climate TRACE: Estimating Global Greenhouse Gas Emissions from Buildings
Created a scalable machine learning model predicting buildings’ Energy Use Intensity (EUI) using limited satellite, climatic, and socioeconomic data. Improved model performance by 54% over baseline, providing a valuable tool for data-driven emissions estimation and supporting more effective emission reduction strategies.