John D. Lafferty
| John D. Lafferty | |
|---|---|
| Residence | Chicago, IL |
| Fields |
Computer Science Machine Learning |
| Institutions |
University of Chicago Carnegie Mellon University IBM Research Harvard University |
| Alma mater | Princeton University |
| Doctoral students |
Adam Berger Cheng Xiang Zhai Xiaojin Zhu |
| Other notable students | David Blei (Post Dr.) |
| Known for | Conditional Random Fields |
| Notable awards |
IEEE Fellow (2007) Test-of-Time Award of ICML (2011,2012) Classic paper prizes of ICML (2013) Test of Time Award of SIGIR (2014) |
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Website galton |
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John D. Lafferty is an American scientist, Louis Block Professor at the University of Chicago and leading researcher in machine learning. He is best known for proposing the Conditional Random Fields with Andrew McCallum and Fernando C.N. Pereira.
Lafferty is currently a full professor at the University of Chicago, and has held visiting positions at the University of California, Berkeley and the University of California, San Diego. His research interests are in statistical machine learning,information retrieval, and natural language processing; focus on computational and statistical aspects of nonparametric methods, high-dimensional data and graphical models.
Prior to University of Chicago in 2011, he was faculty at Carnegie Mellon University since 1994， where he helped to found the world's first machine-learning department. Before CMU, he was a Research Staff Member at IBM Thomas J. Watson Research Center, where he worked on natural speech and text processing in the group led by Frederick Jelinek. Lafferty received a Ph.D. in Mathematics from Princeton University, where he was a member of the Program in Applied and Computational Mathematics. He was an assistant professor in the Mathematics Department at Harvard University before joining IBM.
He was elected Fellow of IEEE in 2007 "for contributions to statistical pattern recognition and statistical language processing".
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