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IST Lunch Bunch

Tuesday, October 15, 2019
12:00pm to 1:00pm
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Annenberg 105
Measuring Economic Development from Space
Stefano Ermon, Assistant Professor, Computer Science, Stanford University,


Recent technological developments are creating new spatio-temporal data streams that contain a wealth of information relevant to sustainable development goals. Modern AI techniques have the potential to yield accurate, inexpensive, and highly scalable models to inform research and policy. A key challenge, however, is the lack of large quantities of labeled data that often characterize successful machine learning applications. In this talk, I will present new approaches for learning useful spatio-temporal models in contexts where labeled training data is scarce or not available at all. I will show applications to predict and map poverty in developing countries, monitor  agricultural productivity and food security outcomes, and map infrastructure access in Africa. Finally, I will discuss opportunities and challenges for using these predictions to support decision making, including techniques calibration and for inferring human preferences from data.

For more information, please contact Diane Goodfellow by email at diane@cms.caltech.edu.