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Seminario: “Artificial Intelligence for Sustainability”

Venerdì 22 Dicembre 2017, ore 10:30 - Aula 1C150 - Stefano Ermon

ARGOMENTI: Seminari

Venerdì 22 Dicembre 2017 alle ore 10:30 in Aula 1C150, Stefano Ermon (Stanford University) terrà un seminario dal titolo “Artificial Intelligence for Sustainability”.

Abstract
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. As a first example, I will present a machine learning method we developed to predict and map poverty in developing countries. Our method can reliably predict economic well-being using only high-resolution satellite imagery. Because images are passively collected in every corner of the world, our method can provide timely and accurate measurements in a very scalable end economic way, and could revolutionize efforts towards global poverty eradication. As a second example, I will present some ongoing work on monitoring food security outcomes.

Bio
Stefano Ermon is an Assistant Professor (tenure track) of Computer Science in the CS Department at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory, and a fellow of the Woods Institute for the Environment. His research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. He has won several awards, including four Best Paper Awards (AAAI, UAI and CP), a NSF Career Award, a Sony Faculty Innovation Award, and a McMullen Fellowship. Stefano earned his Bachelor’s and Master degree in Electrical and Electronics Engineering at University of Padova in 2006 and 2008, respectively. He earned his Ph.D. in Computer Science at Cornell University in 2015.