Sherrie Wang

Sherrie Wang is a Professor and Principal Investigator at Massachusetts Institute of Technology, leading the Earth Intelligence Lab. Her research focuses on developing machine learning methods to monitor planetary systems and advance sustainable development, particularly in low- and middle-income regions where ground truth data is scarce.

She obtained her PhD in Computational and Mathematical Engineering from Stanford University in 2021 under David Lobell, following a Ciriacy-Wantrup Postdoctoral Fellowship at UC Berkeley with Solomon Hsiang and the Global Policy Lab. Her academic work bridges Earth observation, machine learning, and global sustainability, with a focus on agricultural management and climate change mitigation.

Recent publications highlight her leadership in benchmarking vision-language models for Earth data (CVPRW 2024), mapping Clean Water Act-regulated water bodies (Science 2024), and advancing weakly supervised cropland segmentation techniques (Remote Sensing 2020). Her work frequently utilizes satellite imagery, LiDAR, and crowdsourced data to address environmental challenges.

Scientific recognition includes the Best Paper Award at ICLR ML4RS Workshop (2024) and the Sloan Research Fellowship. She collaborates with institutions like USDA, NSF, and Stanford Human-Centered AI, with funding from USAID and the Global Innovation Fund.

Advising and collaboration: She mentors PhD students like Chenhui Zhang and Jordi Laguarta, with notable partnerships at the Stanford Sustainability and AI Lab. Her team's work mapping Thai agricultural systems (MIT News 2024) exemplifies her commitment to real-world impact.