photo of Emily B. Fox
 
Emily B. Fox
    University of Washington

Username:ebfox
 
 
 
 
Home page:http://www.stat.washington.edu/~ebfox
Bio:  

I am currently an assistant professor in the Department of Statistics at the University of Washington. My research interests include Bayesian and nonparametric Bayesian approaches to time-series and longitudinal data analysis, with an emphasis on extensions to high-dimensional data.

Following a two-year postdoc in the Duke Department of Statistical Science working with Prof. Mike West and Prof. David Dunson, I spent a year as an assistant professor in the Wharton Department of Statistics, University of Pennsylvania. In 2009, I received my Ph.D. in the Electrical Engineering and Computer Science (EECS) Department at MIT, working with Prof. Alan Willsky as a member of the Stochastic Systems Group (SSG) within MIT's Laboratory for Information and Decision Systems (LIDS). While pursuing my Ph.D., I collaborated with, among others, Dr. Erik Sudderth, Prof. Michael Jordan, and Dr. John Fisher.

Papers, Presentations and Reports Authored by Emily B. Fox

  1. City-Scale Bayesian Spatial Modeling for House Pricing, Shirley Ren, Emily B. Fox, October, 2015. Posted on 9 Oct 2015.
  2. Scalable Bayes for Large and Streaming Sequential Data, Nick Foti, Emily B. Fox, October, 2015. Posted on 9 Oct 2015.
  3. A Complete Recipe for Stochastic Gradient MCMC, Yian Ma, Tianqi Chen, Emily B. Fox, Neural Information Processing Systems, 7, December, 2015. Posted on 8 Oct 2015.
  4. Q1 2015 TerraSwarm Quarterly Report Milestone #10, Edward A. Lee, Tajana Simunic Rosing, John Wawrzynek, Prabal Dutta, Anthony Rowe, Richard Murray, Jeffrey A. Bilmes, Alberto Sangiovanni-Vincentelli, Sanjit Seshia, Jan Rabaey, Douglas L. Jones, Stephane Lafortune, Alex Halderman, David Blaauw, Roozbeh Jafari, Carlos Guestrin, Emily B. Fox, Rahul Mangharam, George Pappas, Vijay Kumar, Bjoern Hartmann, John D. Kubiatowicz, TerraSwarm Research Center, February, 2015. Posted on 25 Feb 2015.
  5. Streaming Variational Inference for Bayesian Nonparametric Mixture Models, Alex Tank, Nick Foti, Emily B. Fox, International Conference on Artificial Intelligence and Statistics (AISTATS), 9, May, 2015. Posted on 9 Feb 2015.
  6. Stochastic Variational Inference for Hidden Markov Models, Nick Foti, Jason Xu, Dillon Laird, Emily B. Fox, Neural Information Processing Systems (NIPS), 8, December, 2014. Posted on 3 Nov 2014.
  7. City-Scale Bayesian Spatial Modeling for House Pricing, Shirley Ren, Emily B. Fox, 30, October, 2014. Posted on 1 Nov 2014.
  8. Scalable Bayes for Large and Streaming Sequential Data, Nick Foti, Emily B. Fox, 27, October, 2014. Posted on 27 Oct 2014.
  9. Bayesian Dynamic Modeling, Emily B. Fox, 16, October, 2014. Posted on 21 Oct 2014.
  10. Stochastic Gradient Hamiltonian Monte Carlo, Tianqi Chen, Emily B. Fox, Carlos Guestrin, International Conference on Machine Learning, 21, June, 2014. Posted on 27 Apr 2014.

Counts

  • 1 Journal article.
  • 5 Conference papers.
  • 1 Technical report.
  • 2 Talk or presentations.
  • 2 Posters.

The counts above are from the publications database. The number of posters is derived from the presentations.

Note: A poster is a presentation that has the word 'poster' (case-insensitive) in the any of the text fields. Thus, the poster count might be somewhat inaccurate. The number of posters is deducted from the number of presentations and bother are reported.