Raymond Wong

  • Associate Professor | Department of Statistics | Texas A&M University

Short Bio

I am an Associate Professor in the Department of Statistics at Texas A&M University. From 2014 to 2017, I was an Assistant Professor in the Department of Statistics at Iowa State University. I recieved my Ph.D. degree in Statistics from the University of California at Davis in 2014.

Professional Services

  • Associate Editor, Journal of Computational and Graphical Statistics
  • Associate Editor, Journal of the American Statistical Association, Review
  • Editorial Board, Chemometrics and Intelligent Laboratory Systems
  • Executive Committee Member, Research Institute for Foundations of Interdisciplinary Data Science (FIDS)

I was an Associate Editor for the Canadian Journal of Statistics from 2019 to 2021. I was also the Awards Chair for the ASA Section on Statistical Computing and the ASA Section on Statistical Graphics from 2020 to 2023.


News

  • February 2024: Paper on ‘Broadcasted Nonparametric Tensor Regression’ has been accepted by the Journal of the Royal Statistical Society: Series B. [link]
  • February 2024: Paper on ‘Balancing Method for Non-monotone Missing Data’ is now on arXiv. [link]
  • February 2024: Paper on ‘Distributional Off-policy Evaluation with Bellman Residual Minimization’ is now on arXiv. [link]
  • November 2023: Raymond has been selected as a Top Reviewer for the Conference on Neural Information Processing Systems (NeurIPS).
  • October 2023: Saptarshi has been selected as a recipient of NeurIPS Scholar Award. Congratulations!
  • September 2023: Paper on ‘Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data’ has been accepted by the Conference on Neural Information Processing Systems (NeurIPS). [link]
  • September 2023: Paper on ‘Flexible Functional Treatment Effect Estimation’ is now on arXiv. [link]
  • September 2023: Paper on ‘Prediction of Tropical Pacific Rain Rates with Over-parameterized Neural Networks’ is now on arXiv. [link]
  • June 2023: Paper on ‘Projected State-action Balancing Weights for Offline Reinforcement Learning’ has been accepted by the Annals of Statistics. [link]
  • May 2023: Paper on ‘Hierarchical Nuclear Norm Penalization for Multi-view Data’ has been accepted by Biometrics. [link]
  • May 2023: Jiangyuan has passed his Ph.D. final exam. He will join Google as a Data Scientist starting this July. Congratulations!
  • March 2023: Paper on ‘Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior’ has been accepted by Technometrics. [link]