Raymond Wong

  • Associate Professor, Department of Statistics, Texas A&M University
Raymond is an Associate Professor in the Department of Statistics, Texas A&M University. His research focuses on statistical problems with modern data complications such as enormous volume, large dimensionality, and manifold structures.
He is an Executive Committee Member of the Research Institute for Foundations of Interdisciplinary Data Science (FIDS), funded by the NSF TRIPODS Initiative. He is also an Associate Editor of the Canadian Journal of Statistics and the Journal of Computational and Graphical Statistics. In addition, he serves as the Awards Chair of both the ASA Section on Statistical Computing and the ASA Section on Statistical Graphics.

News

  • September 2021: Our paper on 'Implicit Sparse Regularization: The Impact of Depth and Early Stopping' has been accepted by the Conference on Neural Information Processing Systems (NeurIPS). [link]
  • September 2021: Our paper on 'Projected State-action Balancing Weights for Offline Reinforcement Learning' is now on arXiv. [link]
  • August 2021: Jiayi has been selected as the recipient of the Emanuel Parzen Graduate Research Fellowship Award. Congratulations!
  • May 2021: Our paper on 'Matrix Completion with Model-free Weighting' has been accepted by the International Conference on Machine Learning (ICML). [link]
  • March 2021: Our paper on 'Estimation of Partially Conditional Average Treatment Effect by Hybrid Kernel-covariate Balancing' is now on arXiv. [link]
  • February 2020: Our paper on 'Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis' has been accepted by the IEEE Transactions on Information Theory. [link]
  • January 2021: Raymond has been appointed as an Associate Editor of the Journal of Computational and Graphical Statistics.