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Kevin Leyton-Brown, "An Electronic Market for Agricultural Trade in Uganda "
Most adults in developing countries (e.g., 80% of Ugandans) are farmers. In such parts of the world, market inefficiency is a significant societal problem, arising substantially from poor access to information and other power differentials between farmers and buyers. Kudu is an electronic market for agricultural trade in developing countries designed to increase efficiency. Farmers and buyers enter bids using SMS and USSD, the messaging technologies available on non-internet-enabled phones. Kudu automatically identifies profitable trades and proposes them to participants by text message. As a positive side effect, Kudu infers accurate information about prevailing prices, which it broadcasts widely. For the past two years Kudu has been piloted in Uganda. Tens of thousands of users have registered with the system, and at least $2 million USD in crops have been traded. This talk will focus on the computational, incentive, and practical challenges we have faced designing a market in this unique setting.

Kevin Leyton-Brown is a professor of Computer Science at the University of British Columbia and an associate member of the Vancouver School of Economics. He holds a PhD and M.Sc. from Stanford University (2003; 2001) and a B.Sc. from McMaster University (1998). He studies the intersection of computer science and microeconomics, addressing computational problems in economic contexts and incentive issues in multiagent systems. He also applies machine learning to the automated design and analysis of algorithms for solving hard computational problems.

He has co-written two books, "Multiagent Systems" and "Essentials of Game Theory," & 100+ peer-refereed technical articles; his work received over 8,000 citations and an h-index of 37. He is the recipient of UBC's 2015 Charles A. McDowell Award for Excellence in Research, a 2014 NSERC E.W.R. Steacie Memorial Fellowship—a 2013 Outstanding Young Computer Science Researcher Prize fr. Canadian Association of Computer Science.

Oct 20, 2017 1:30 PM in Eastern Time (US and Canada)

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