**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

Apr 30, 2021 | Defended my PhD in statistics! |

Feb 17, 2021 | Package multChernoff computes finite-sample tail bounds of multinomial LRT. |

Dec 3, 2020 | Package InvariantCausal.jl upgraded to Julia 1.x. |

Oct 19, 2020 | Article 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. |