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.

Recent activities

The University recently approved the Committee on Computational and Applied Mathematics. We are recruiting the first group of Ph.D. students into this program.

Rina Foygel Barber, Chao Gao, 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 taught 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 recently celebrated its 60th anniversary. We organized a workshop in connection with the 2016 Bahadur lectures.

In September 2016 we ran a workshop at the Becker-Friedman Institute for Research in Economics on the theme Machine Learning: What's in it for Economics?

Here are some slides from a recent research talk

Recent publications and preprints

  • Convergence analysis for rectangular matrix completion using Burer-Monteiro factorization and gradient descent
    Qinqing Zheng and John Lafferty

  • Denoising flows on trees
    Sabyasachi Chatterjee and John Lafferty

  • Adaptive risk bounds in unimodal regression
    Sabyasachi Chatterjee and John Lafferty

  • Quantized nonparametric estimation
    Yuancheng Zhu and John Lafferty


  • Stat 41600, High Dimensional Statistics II (Spring, 2016, with Rina Foygel Barber). Syllabus

  • Stat 31080, Numerical Methods in Statistics and Applied Mathematics (Winter, 2017). Syllabus

Research support

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).