Remote Sensing Scientist
Current• Lead developer for implementation of novel forest biomass model for NASA spaceborne lidar mission. • Achieved 10x improvement in model computation with new Python implementation.• Successfully scaled model for global application using NASA cloud platform; leveraged cloud implementation to build end-to-end pipeline from spatiotemporal query to local PostGIS database.• Planned, conducted, and wrote statistical study of global tree architecture to improve remote-sensing-based biomass estimates; lead author of paper under review at Environmental Research: Ecology.• Presented key findings to NASA project leads at 2023 GEDI Science Team meeting.