Jun Yang

ABOUT ME

I am a Ph.D Candidate in Statistics at University of Toronto, advised by Daniel M. Roy and Jeffrey S. Rosenthal. I am affiliated with the Department of Statistical Sciences since Fall 2014, and the Vector Institute since Fall 2017. Besides, I was a visiting student researcher at Simons Institute, UC Berkeley in Spring 2017.

I got my M.Sc. in Applied Maths from Queen's University adviced by Fady Alajaji and Glen Takahara and B.Eng. in Electronic Engineering from Tsinghua University.

RESEARCH

My current research interests include statistical learning theory, computational statistics, Bayesian inference, and applied probability.

Recent work:
• Optimal Scaling for Metropolis Algorithms on General Target Distributions
  (with Gareth O. Roberts and Jeffrey S. Rosenthal)
• Spectral Inference under Complex Temporal Dynamics
  (with Zhou Zhou)
• Complexity Results for MCMC derived from Quantitative Bounds
  (with Jeffrey S. Rosenthal)
  | arXiv:1708.00829 | slides
• A Bayesian Decision-Theoretic Analysis of Bayesian Inference under Model Misspecification
  (with Daniel M. Roy and Yanbo Tang)
  | slides
• On Bounding the Union Probability using Partial Weighted Information
  (with Fady Alajaji and Glen Takahara)
  Statistics and Probability Letters, 116, 38–44, 2016.
  | arXiv:1506.08331 (recommended) | pdf | supplement | slides
• Lower Bounds on the Probability of a Finite Union of Events
  (with Fady Alajaji and Glen Takahara)
  SIAM Journal on Discrete Mathematics, 30(3), 1437–1452, 2016.
  | arXiv:1401.5543 | pdf (recommended) | slides

OTHERS

Activities, teaching, non-work page (under construction).