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SUMMARY:Artificial Intelligence for Sustainability
DTSTART:20180628T133000
DTEND:20180628T163000
DTSTAMP:20260429T121454Z
UID:04a1b72714d481ba4b53668b121e82a75e9b8f00bac01dc6ad406921
CATEGORIES:Conferences - Seminars
DESCRIPTION:Stefano Ermon\nRecent technological developments are creating 
 new spatio-temporal data streams that contain a wealth of information rele
 vant to sustainable development goals. Modern AI techniques have the poten
 tial to yield accurate\, inexpensive\, and highly scalable models to infor
 m research and policy. A key challenge\, however\, is the \nlack of large
  quantities of labeled data that often characterize successful machine lea
 rning applications.\nIn this talk\, I will present new approaches for lear
 ning useful spatio-temporal models in contexts where labeled training data
  is scarce or not available at all. I will show applications to predict an
 d map poverty in developing countries\, monitor  agricultural productivit
 y and food security outcomes\, and map infrastructure access in Africa. Ou
 r methods can reliably predict economic well-being using only high-resolut
 ion satellite imagery. Because images are passively collected in every cor
 ner of the world\, our methods can provide timely and accurate measurement
 s in a very scalable end economic way\, and could revolutionize efforts to
 wards global poverty eradication.\n\nStefano Ermon is an Assistant Profess
 or of Computer Science in the CS Department at Stanford University\, where
  he is affiliated with the Artificial Intelligence Laboratory\, and a fell
 ow of the Woods Institute for the Environment. His research is centered on
  techniques for probabilistic modeling of data\, inference\, and optimizat
 ion\, and is motivated by a range of applications\, in particular ones in 
 the emerging field of computational sustainability. He has won several awa
 rds\, including four Best Paper Awards (AAAI\, UAI and CP)\, a NSF Career 
 Award\, an ONR Young Investigator Award\, a Sony Faculty Innovation Award\
 , an AWS Machine Learning Award\, a Hellman Faculty Fellowship\, and the I
 JCAI Computers and Thought Award. Stefano earned his Ph.D. in Computer Sci
 ence at Cornell University in 2015.
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
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