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Computational epidemiology tutorial featured at ACM Knowledge Discovery and Data Mining Conference

August 22, 2014

GBCB faculty members Dr. Madhav Marathe and Dr. Anil Vullikanti will present a tutorial on computational epidemiology, along with Thomas L. Phillips Professor of Engineering Naren Ramakrishnan, at the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining on August 24th, 2014 in New York City.

As recent pandemics such as H1N1 and the Ebola outbreak have shown, diseases spread very fast in today’s interconnected world, making public health an important research area. How can an outbreak be contained before it becomes an epidemic, and what disease surveillance strategies should be implemented?

In this tutorial, the researchers will approach epidemics based on diffusion processes on complex networks, which are able to capture more realistic problems. They will provide a state of the art overview of computational epidemiology, a multi-disciplinary research area that overlaps different areas in computer science, including data mining, machine learning, high performance computing and theoretical computer science, as well as mathematics, economics and statistics.

KDD 2014 is a premier interdisciplinary conference, bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics and big data. This year’s conference theme is ‘Data Science for Social Good’.


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