Next Thursday – not broadcast, not taped…
UNIVERSITY OF WASHINGTON
Computer Science and Engineering
COLLOQUIUM
SPEAKER: Chris Re, University of Wisconsin, Madison
TITLE: Making Applications that use Statistical Analysis Easier to
Build and Maintain
DATE: Thursday, February 21, 2013
TIME: 3:30pm
PLACE: EEB-105
HOST: Magdalena Balazinska
ABSTRACT:
NOTE: This talk will NOT be broadcast live, and will not be taped except
for internal CSE use!
The question driving my work is: How should one deploy statistical data-
analysis tools to enhance data-driven systems? Even partial answers to
this question may have a large impact on science, government, and
industry—each of whom are increasingly turning to statistical techniques
to get value from their data.
To understand this question, my group has built or contributed to a
diverse set of data-processing systems: a system called GeoDeepDive that
reads and answers questions about the geology literature and is used by
geologists to gain insights into the Earth’s carbon cycle; a muon filter
that is used in the IceCube neutrino telescope to process over 250 million
events each day in the hunt for the origins of the universe; and a host of
enterprise analytics applications with Oracle and EMC/Greenplum. Even
within this diverse set, we have found common abstractions, which can be
used to build and maintain such systems in a more cost-effective way. In
this talk, I will describe some of these abstractions along with the
theoretical and algorithmic questions that they raise. Finally, I will
describe my vision of how and why classical data management will continue
to play an important role in the age of statistical data analysis.
Papers, software, virtual machines that contain installations of our
software, links to applications that are discussed in this talk, and our
list of collaborators are available from http://www.cs.wisc.edu/hazy
We also have a YouTube channel:
http://www.youtube.com/HazyResearch with videos about our projects.
Bio:
Christopher (Chris) Re is an assistant professor in the department of
computer sciences at the University of Wisconsin-Madison. The goal of his
work is to enable users and developers to build applications that more
deeply understand and exploit data. Chris received his PhD from the
University of Washington in Seattle under the supervision of Dan Suciu.
For his PhD work in probabilistic data management, Chris received the
SIGMOD 2010 Jim Gray Dissertation Award. Chris’s papers have received four
best-paper or best-of-conference citations, including best paper in PODS
2012, best-of-conference in PODS 2010 twice, and one best-of- conference
in ICDE 2009). Chris received an NSF CAREER Award in 2011.
Refreshments to be served in room prior to talk.
*NOTE* This lecture will be broadcast live via the Internet. See
http://www.cs.washington.edu/news/colloq.info.html for more information.
Email: talk-info@cs.washington.edu
Info: http://www.cs.washington.edu/
(206) 543-1695
The University of Washington is committed to providing access, equal
opportunity and reasonable accomodation in its services, programs,
activities, education and employment for individuals with disabilities.
To request disability accommodation, contact the Disability Services
Office at least ten days in advance of the event at: (206) 543-6450/V,
(206) 543-6452/TTY, (206) 685-7264 (FAX), or email at
dso@u.washington.edu.
