Big Data for Computational Science and Engineering

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In this video from the SIAM Conference on Computational Science and Engineering, David Bader from Georgia Tech and Tamara Kolda from Sandia discuss the significance of Big Data and the importance of mathematical modeling to make sense of and interpret all that data in various fields from social networks and epidemiology to climatology.

The SIAM CS&E conference seeks to enable in-depth technical discussions on a wide variety of major computational efforts on large problems in science and engineering, foster the interdisciplinary culture required to meet these large-scale challenges, and promote the training of the next generation of computational scientists.