Benjamin Bloem-Reddy

Benjamin Bloem-Reddy

Bayesian nonparametrics, probabilistic modeling and inference

I am a Postdoctoral Research Assistant in Statistical Machine Learning. 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 like partitions and permutations. I am generally interested in all aspects of machine learning, both theoretical and applied.



  • B. Bloem-Reddy , A. Foster , E. Mathieu , Y. W. Teh , Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks, in Conference on Uncertainty in Artificial Intelligence, 2018.


  • B. Bloem-Reddy , Discussion of F. Caron and E. B. Fox, "Sparse graphs using exchangeable random measures.", Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 79, no. 5, 2017.
  • B. Bloem-Reddy , P. Orbanz , Preferential Attachment and Vertex Arrival Times, Oct. 2017.
  • B. Bloem-Reddy , E. Mathieu , A. Foster , T. Rainforth , H. Ge , M. Lomelí , Z. Ghahramani , Y. W. Teh , Sampling and inference for discrete random probability measures in probabilistic programs, NIPS Workshop on Advances in Approximate Bayesian Inference, 2017.


  • B. Bloem-Reddy , J. P. Cunningham , Slice Sampling on Hamiltonian Trajectories, in International Conference on Machine Learning (ICML), 2016, vol. 33, 3050—3058.
  • B. Bloem-Reddy , P. Orbanz , Random Walk Models of Network Formation and Sequential Monte Carlo Methods for Graphs, Dec. 2016.