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.