Residence Chicago, IL | Name John Lafferty Alma mater Princeton University | |
Institutions University of Chicago
Carnegie Mellon University
IBM Research
Harvard University Doctoral students Adam Berger
Cheng Xiang Zhai
Xiaojin Zhu 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) Fields Computer Science, Machine learning Institution University of Chicago, Carnegie Mellon University, IBM Research, Harvard University | ||
Other notable students David Blei(Post Dr.) | ||
John D. Lafferty is an American scientist, Professor at Yale University and leading researcher in machine learning. He is best known for proposing the Conditional Random Fields with Andrew McCallum and Fernando C.N. Pereira.
Contents
Biography
Lafferty is currently a full professor at Yale University, and has held visiting positions at the University of Chicago, 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".
Academic career
Lafferty served many prestigious positions, including: 1) program co-chair and general co-chair of the Neural Information Processing Systems (NIPS) Foundation conferences; 2) co-director of CMU's new Ph.D. Machine Learning Ph.D. Program; 3) associate editor of the Journal of Machine Learning Research (JMLR) and the Electronic Journal of Statistics; and 4) member of the Committee on Applied and Theoretical Statistics (CATS) of the National Research Council.
Lafferty received numerous awards, including two Test-of-Time awards at the International Conference on Machine Learning (ICML) 2011 & 2012, classic paper prize of ICML 2013, and Test-of-Time awards at the Special Interest Group on Information Retrieval (SIGIR) 2014.