Prof. Sherrie Wang

Sherrie Wang’s research uses novel data and computational algorithms to monitor our planet and enable sustainable development. Her focus is on improving agricultural management and mitigating climate change, especially in low- or middle-income regions of the world. To this end, she frequently uses satellite imagery, crowdsourced data, LiDAR, and other spatial data. Due to the scarcity of ground truth data in these regions and the noisiness of real-world data in general, her methodological work is geared toward developing machine learning methods that work well with these constraints.

Prior to MIT, Wang was a Ciriacy-Wantrup Postdoctoral Fellow at UC Berkeley, hosted by Solomon Hsiang and the Global Policy Lab. In 2021, she obtained her PhD in Computational and Mathematical Engineering from Stanford University, where she was advised by David Lobell and benefited from mentors at the Center on Food Security and the Environment and the Sustainability and AI Lab.