Research Interests
Apply multi-petabyte catalogs of satellite imagery and geospatial datasets for planetary-scale analysis of Earth's surface environments including air pollution, weather and climate, land use and land cover through Google Earth Engine;
Develop land use regression modeling algorithms that incorporate multiple types of measurements into a single modeling frame for the purpose of creating high spatial (e.g., 30m) and temporal (e.g., daily, monthly and annual) resolution air pollution surfaces;
Investigate associations of respiratory symptoms with environmental exposure through machine learning techniques and biostatistics analyses.