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.
My research is in statistical machine learning, with a current 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 and
building new search tools for the published scientific literature. Hopper is supported by a grant from
the Alfred P. Sloan Foundation.
During summer 2016 I'll be teaching a minicourse at Columbia on high dimensional statistical learning.
A report was prepared from a 2014 NRC workshop we organized on
training students to extract value from big data.
The University of Chicago Department of Statistics is celebrating its 60th anniversary this spring. We organized a
workshop in connection with the 2016 Bahadur lectures.
In September 2016 we are running a workshop at the Becker-Friedman Institute for Research in Economics on the theme Machine Learning: What's in it for Economics?
Recent publications and preprints
Selective inference for group-sparse linear models
Fan Yang, Rina Foygel Barber, Prateek Jain, and John Lafferty
The research of my group is currently supported by grants from the National Science Foundation, the Alfred P. Sloan Foundation, the Office of Naval Research, DARPA, Amazon AWS in Education Machine Learning, and Facebook (AI/ML).