“Identifiable Deep Generative Models via Sparse Decoding”, presented by Gemma Moran, Postdoctoral Research Scientist, Data Science Institute, Columbia University.
Author: Yuan, Yelie
Statistics Colloquium: Richard Guo, University of Cambridge
“Harnessing Extra Randomness: Replicability, Flexibility and Causality”, presented by Richard Guo, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge.
Statistics Colloquium: Matteo Bonvini, Carnegie Mellon University
“Optimal Subgroup Identification”, presented by Matteo Bonvini, Department of Statistics and Data Science, Carnegie Mellon University.
Statistics Colloquium: Guanyu Hu, University of Missouri
“Bayesian Spatial Homogeneity Learning for Functional Data”, presented by Guanyu Hu, Department of Statistics, University of Missouri.
Statistics Colloquium: Ying Zhou, University of Toronto
“The Promises of Parallel Outcomes”, presented by Ying Zhou, Department of Statistics, University of Toronto.
Statistics Colloquium: Mary Lai Salvana, University of Houston
“3D Bivariate Spatial Modelling of Argo Ocean Temperature and Salinity Profiles”, presented by Mary Lai Salvana, Postdoctoral Fellow, Department of Mathematics, University of Houston.
Adjunct Prof. Joseph Cappelleri wins HPSS Long-Term Excellence Award
Congratulations to Adjunct Professor Joseph Cappelleri for receiving the Health Policy Statistics Section (HPSS) Long-Term Excellence Award! The award recognizes significant contributions to health care policy and health services research through mentoring and/or service that advance the aims of HPSS.
PhD student Yelie Yuan received an honorable mention for the John M. Chambers Statistical Software Award
PhD student Yelie Yuan’s R package wdnet, co-authored with Prof. Tiandong Wang, Prof. Jun Yan, and Prof. Panpan Zhang, has received an honorable mention for the 2023 John M. Chambers Statistical Software Award. The package provides functions for analyzing weighted, directed networks, all of which are based on recent research and are not available in other packages. […]
Statistics Colloquium: Marcin Jurek, University of Texas at Austin
“Gaussian Processes as a Tool to Represent Complex Phenomena”, presented by Marcin Jurek, Department of Statistics and Data Sciences, University of Texas at Austin.
Statistics Colloquium: Nathan Wikle, University of Texas at Austin
“Causal Inference for Environmental Health Data: Estimating Causal Effects in the Presence of Spatial Interference”, presented by Nathan Wikle, Department of Statistics and Data Sciences, University of Texas at Austin.