Richard Guo
Department of Statistics. University of Washington, Seattle.
I am a PhD candidate in statistics. I work on problems related to causal inference. My advisor is Thomas Richardson.
I am interested in addressing various statistical challenges posed by causal inference, such as inference under non-standard asymptotics, finite sample, irregularity, and partial identifiability. I am also interested in approaches that enhance efficiency and interpretability, such as Bayes, empirical Bayes and graphical models.
Previously, I studied computer science at Duke and MIT.
news
Dec 3, 2020 | Package InvariantCausal.jl upgraded to Julia 1.x. |
Oct 19, 2020 | Another preprint with Ema on optimal set-identification of causal effects. |
Aug 10, 2020 | New preprint with Ema on efficient causal estimation under linearity. |
Aug 4, 2020 | Non-nested (causal) model selection paper appears on Biometrika. |
Jul 5, 2020 | Teaching undergraduate probability I and II this summer. |
May 15, 2020 | Presenting my work with Ema at the UW statistics seminar. |
May 6, 2020 | Presenting the spectral empirical Bayes work at the CSSS. |
Mar 19, 2020 | New preprint on multinomial concentration. |