John Lafferty

Louis Block Professor

Departments of Statistics, Computer Science, and the College

John Lafferty’s research focuses on nonparametric methods, sparsity, analysis of high-dimensional data, graphical models, information theory, and applications in language processing, computer vision, and information retrieval. He specializes in machine learning, which combines the power of statistics and computation.

An associate editor of the Journal of Machine Learning Research, Lafferty also served as a general cochair of the 2010 Neural Information Processing Systems Foundation conference. His research has been supported by the National Science Foundation, Advanced Research and Development Activity of the U.S. Intelligence Community, Defense Advanced Research Projects Agency, Air Force Office of Scientific Research, and Google.

Lafferty received his doctoral degree in mathematics from Princeton University, where he was a member of the Program in Applied and Computational Mathematics. He served on the mathematics faculty at Harvard University, then became a research staff member of the IBM Thomas J. Watson Research Center, where he worked on statistical natural language processing. Most recently he was professor of computer science, machine learning, and statistics at Carnegie Mellon University.

Lafferty joined the University of Chicago faculty in 2011.

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