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ANC/DTC Seminar: John Quinn, Makerere University

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Machine learning applications in developing-world sustainability

  • ANC/DTC Seminar
When Aug 12, 2014
from 11:00 AM to 12:00 PM
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Cheap computing hardware and network capacity in the developing world have created significant new data analysis opportunities relevant to sustainability. I will talk about some of the ways in which machine learning techniques can be applied in this context, with a particular focus on disease mapping but touching on other applications. First, the collection of some information that previously required the judgement of scarce human experts can now be done automatically on a large scale, for example by using camera enabled mobile devices to diagnose disease in humans and crops. Second, diverse and unconventional sources of information can be combined, for example by combining remote sensing imagery, natural language data and crowdsourced observations to better anticipate disease burden. I will illustrate these ideas by describing systems  being fielded in Uganda.


Bio: John Quinn is a Data Scientist in the United Nations Global Pulse lab in Kampala, and a Senior Lecturer in the Department of Computer Science at Makerere University, Uganda. At Makerere he runs the AI-DEV research group, which studies the use of artificial intelligence techniques in health, agriculture and resource allocation problems.