Big Data arises from many frontiers of scientific research
and decision and policy making. It holds great promise for
the discovery of heterogeneity in the population for
personalized treatments and services as well as possibly
weak patterns in possibly heterogeneous populations.
It involves any voluminous amount of structured,
semi-structured and unstructured data that has the
potential to be mined for information. Big Data is an
interdisciplinary area that requires collaborations and
cross-fertilizations among Applied Mathematics, Computer
Science, and Statistics. Recognizing the importance of Big
Data, IAS organized the IMA-HK-IAS Joint Program on
Statistics and Computational Interface to Big Data on
4 -16 January 2015, receiving co-sponsorships from the
Institute for Mathematics and its Applications (IMA) at the
University of Minnesota, the Center for Statistical Science,
the Department of Mathematics and the Department of
Computer Science & Engineering at HKUST.
Coordinated by IAS Visiting Professor Jianqing Fan from
Princeton University, IAS Visiting Professor Thomas Hou
from California Institute of Technology, Prof Bingyi Jing
from HKUST and Prof Eric Xing from the Carnegie Mellon
University, the program brought together 22 keynote
speakers and 25 invited speakers from Applied
Mathematics, Computer Science and Statistics to share
their research findings. The program includes two short
courses, a 6-day workshop and a 1-day mini-workshop,
attracting over 140 participants from Hong Kong and
overseas.
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Event Highlights
Feb 2015
