Christopher (Chris) Ré is currently 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 data. In
many applications, machines can only understand the meaning of data
statistically, e.g., user-generated text or data from sensors. To
attack this challenge, Chris's recent work is to build a system, Hazy,
that integrates a handful of statistical operators with a standard
relational database management system.

Chris received his PhD from the University of Washington, Seattle
under the supervision of Dan Suciu. For his PhD work in the area of
probabilistic data management, Chris received the SIGMOD 2010 Jim Gray
Dissertation Award. His PhD work produced two systems: Mystiq, a
system to manage relational probabilistic data, and Lahar, a streaming
probabilistic database. The contributions of these systems are
techniques to efficiently evaluate queries on probabilistic data, such
as multisimulation and extensional plans for aggregates, and to
efficiently represent probabilistic data using materialized views and
approximate lineage.

Chris's papers have received three best-of-conference awards (two in
PODS 2010 and one in ICDE 2009). Chris was recently granted his first
patent.