- Research Program Mentor
PhD candidate at Stanford University
computer vision for remote sensing, causal inference for climate impacts, machine learning and data science, environmental science, sustainable development, biology, AI/ML, comp sci, data science, data mining, data visualization, Remote Sensing, Computer Vision, climate change
BioJeff is a Ph.D. student in the Department of Earth System Science at Stanford. His research applies causal inference and computational methods to understand the impacts of environmental change and improve decision making under climate uncertainty. He is currently focused on quantifying and developing strategies to mitigate the impacts of wildfires. He co-leads the AI Blindspot initiative, which was developed during the Assembly program hosted by the Berkman Klein Center at Harvard University. Prior to Stanford, he was a data science team lead at Pixability and a data scientist at Tesla. Jeff holds a Bachelors in Economics from Wharton and a Masters in Environmental Studies from the University of Pennsylvania.
Computer vision for understanding environmental change
Satellite imagery has become increasingly available and provides opportunities to better understand ecosystem dynamics in near real-time. However, the sheer amount of remotely sensed data available makes it challenging to analyze and interpret patterns. By applying computer vision techniques to satellite imagery, we may be able to better identify signals that can help researchers and scientists understand meaningful changes in the envior