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 also spent Spring 2017 at UC Berkeley as a visiting student researcher.

Before coming to Toronto, I got B.Eng. from Tsinghua University, D.Eng. from Chinese Academy of Sciences, both in electrical engineering, and M.Sc. in applied mathematics from Queen's University in Kingston, advised by Fady Alajaji and Glen Takahara.

I am grateful to be partly supported by Alexander Graham Bell Canada Graduate Scholarship (CGS D).

RESEARCH

I am currently interested in Bayesian inference, statistical learning, computational statistics, non-stationary time series analysis.

Recent work:
• Complexity Results for MCMC Derived from Quantitative Bounds
  Jun Yang and Jeffrey S. Rosenthal
  | arXiv:1708.00829
• Asymptotic Spectral Theory for Locally Stationary Time Series
  (with Zhou Zhou)
• A Bayesian Decision-Theoretic Analysis of Bayesian Inference under Model Misspecification
  (with Daniel M. Roy)
• On Bounding the Union Probability using Partial Weighted Information
  Jun Yang, Fady Alajaji, and Glen Takahara
  Statistics and Probability Letters 116, 38–44, 2016.
  | arXiv:1506.08331 | pdf | supplement
• Lower Bounds on the Probability of a Finite Union of Events
  Jun Yang, Fady Alajaji, and Glen Takahara
  SIAM Journal on Discrete Mathematics 30 (3), 1437–1452, 2016.
  | arXiv:1401.5543 | pdf