Data Science Associate II
John Brandt is a Data Science Associate II in the Restoration team at WRI. He works on developing novel datasets to monitor forest and landscape restoration activities with remote sensing. This work analyzes petabytes of optical and radar satellite imagery with computer vision and deep learning approaches. John is the author of more than a dozen peer reviewed publications on machine learning applications in climate change research, and is a member of WRI's Land and Carbon Lab.
John's background is in machine learning and large-scale environmental modeling. Prior to joining WRI, John held academic and professional positions in water resource and biogeochemical modeling as well in large-scale financial modeling. He holds a Masters in Environmental Management from Yale University, and a B.A. in Biology from Vassar college.
Global Restoration Initiative
WRI is partnering with governments, businesses, and communities around the world to restore millions of hectares of deforested and degraded land.Part of Forests
TerraMatch connects local land restoration champions to capital and technical assistance through a trusted online system that vets their work, supports their growth, and monitors their progress.Part of Forest and Landscape Restoration
Land & Carbon Lab
This initiative connects those at the vanguard of land monitoring with those at the frontlines of land use decisions.Part of Forests