David Blei

From Wikipedia, the free encyclopedia
Jump to: navigation, search
David Blei
Residence United States
Nationality United States
Fields Artificial Intelligence
Institutions Princeton University
Columbia University
Alma mater Brown University B.S. (1997)
University of California, Berkeley Ph.D. (2004)
Doctoral advisor Michael I. Jordan (Berkeley)
Doctoral students Jordan Boyd-Graber
Jonathan Chang
Lauren Hannah
Matt Hoffman
Known for Topic models
Notable awards PECASE
ACM Fellow (2015)
Website
www.cs.columbia.edu/~blei/

David Blei is a Professor in the Statistics and Computer Science departments at Columbia University. Prior to fall 2014 he was an Associate Professor in the Department of Computer Science at Princeton University. His work is primarily in machine learning.

Research[edit]

His research interests include topic models and he was one of the original developers of latent Dirichlet allocation. As of November 11, 2015, his publications have been cited 31,135 times, giving him an h-index of 53.[1]

Honors and Awards[edit]

He was named Fellow of ACM "For contributions to the theory and practice of probabilistic topic modeling and Bayesian machine learning" in 2015.[2]

References[edit]

  1. ^ "David Blei - Google Scholar Citations". scholar.google.com. Retrieved 2015-11-11. 
  2. ^ "ACM Fellows Named for Computing Innovations that Are Advancing Technology in the Digital Age". ACM. 8 December 2015. Retrieved 9 December 2015. 

External links[edit]