Benjamin Bloem-Reddy

I am a Postdoctoral Research Assistant in Statistical Machine Learning in the CSML group, based in the Department of Statistics at the University of Oxford. Previously, I completed my Ph.D. in Statistics at Columbia University, where I was advised by Peter Orbanz.

My research focuses on probabilistic and statistical analysis of networks and other discrete data. In particular, I work on probabilistic models, estimation, and inference for objects like graphs, partitions, and permutations. I am generally interested in all aspects of machine learning, both theoretical and applied — especially the intersection of the two.

I completed my B.S. in Physics at Stanford University, and my M.S. in Physics at Northwestern University, where I worked in the lab of William P. Halperin. Prior to studying at Columbia, I worked for three years as a research analyst at The Brattle Group in Washington, D.C.

Contact: benjamin dot bloem-reddy at
Office: Department of Statistics, Room 1.06

(I recently changed my surname from Reddy to Bloem-Reddy.)


Workshop contributions
  • Random walk models of sparse graphs and networks.
    B. Reddy and P. Orbanz
  • Discussion of F. Caron and E. B. Fox, "Sparse graphs using exchangeable random measures."
    B. Bloem-Reddy
    Journal of the Royal Statistical Society, Series B, 79, Part 5.
    [pdf] [slides from discussion at RSS meeting]

Selected talks

  • Random walk models of networks: modeling and inferring complex dependence.
    Workshop on Bayesian Methods for Networks, Isaac Newton Institute, Cambridge, UK, July 2016.
  • Slice Sampling on Hamiltonian Trajectories.
    ICML, New York, June 2016.