I am a professor at the University of Chicago, with a joint
appointment in Statistics (primary) and Computer Science, and a
faculty member of the
College of the University of Chicago,
currently serving on the College Council. I am also
an Adjoint Professor at the Toyota Technological Institute at Chicago.
Prior to joining the University of Chicago
in 2011, I was Professor of Computer Science, Machine Learning, and
Statistics at Carnegie Mellon University.
My research is in statistical machine learning, with a focus on
computational and statistical aspects of nonparametric methods,
high-dimensional data, graphical models, and document and text analysis.
I'm part of the Computational and
Applied Mathematics Initiative (CAMI) at the University of Chicago.
A short NSF-style biographical sketch is here.
Rina Foygel Barber,
Tracy Ke, and I organize a
research and reading group at the University of Chicago called
HELIOS (High-dimensional Estimation, Learning, Inference and
Optimization in Statistics).
Dave Blei and I have launched the
Hopper project to study statistical machine learning algorithms for
extracting representations of text and mathematical expressions in the
published scientific literature. Hopper is funded by a grant from
the Alfred P. Sloan Foundation.
Postdoctoral position in statistical machine learning
Princeton conference on optimization and learning
Obergurgl conference on AI and theorem proving
Columbia course on high dimensional statistics and learning (Summer 2016)
Training students to extract value from big data (Summary of 2014 Workshop)
Recent publications and preprints