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BEGIN:VEVENT
UID:4393cef2-6451-4901-bf2a-0482f13eb292@community.ucla.edu
SUMMARY:Applications of Machine Learning to the Targeting of Humanitarian A
	id
DTSTAMP:20231220T221000Z
DTSTART:20240206T210000Z
DTEND:20240206T223000Z
DESCRIPTION:Joshua Blumenstock\, PhD\, Chancellor's Associate Professor\, S
	chool of Information and Goldman School of Public Policy\, UC Berkeley\nTa
	rgeting is a central challenge in the design of humanitarian programs: giv
	en available data\, how does one identify the individuals and households w
	ith the greatest need for humanitarian aid?\n\nIn this talk\, Blumenstock 
	will show that machine learning\, applied to non-traditional data from sat
	ellites and mobile phones\, can improve the targeting of anti-poverty prog
	rams. His team's analysis is based on data from three field-based projects
	—in Togo\, Afghanistan\, and Kenya—that illustrate the promise\, as well a
	s some of the potential challenges\, of this new approach to targeting. Co
	llectively\, the results highlight the potential for new data sources to i
	mprove humanitarian response efforts\, particularly in crisis settings whe
	n traditional data are missing or out of date.\n\nThis talk will be held i
	n person and via Zoom.\n\nLight refreshments will be served.\n\nEvent Webs
	ite: https://www.library.ucla.edu/visit/events-exhibitions/applications-of
	-machine-learning-to-the-targeting-of-humanitarian-aid-02-06-24\n\nEvent W
	ebsite: https://ucla.zoom.us/webinar/register/WN_ocA9SyCWS9utPupQ5zT9cw#/r
	egistration\n\nSource: https://community.ucla.edu/event/4393cef2-6451-4901
	-bf2a-0482f13eb292
LOCATION:Charles E. Young Research Library\, Main Conference Room 11360 - h
	ttps://ucla.zoom.us/webinar/register/WN_ocA9SyCWS9utPupQ5zT9cw#/registrati
	on
STATUS:CONFIRMED
TRANSP:TRANSPARENT
X-MICROSOFT-CDO-BUSYSTATUS:FREE
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