## Bayesian Functional Principal Component Analysis using Relaxed Mutually Orthogonal Processes

Sponsor(s):
Statistical Science

Friday, September 09, 2022

3:30 pm - 4:30 pm

James Matuk, Postdoctoral Associate, Duke University

## Semiparametric discrete data regression with Monte Carlo inference and prediction

Sponsor(s):
Statistical Science

Friday, September 16, 2022

3:30 pm - 4:30 pm

Daniel Kowal, Dobelman Family Assistant Professor Department of Statistics, Rice University

## Unsupervised tree boosting for learning probability distributions

Sponsor(s):
Statistical Science

Friday, September 23, 2022

3:30 pm - 4:30 pm

Li Ma, Associate Professor of Statistical Science, Duke University

## Algorithmic Stochastic Localization for the Sherrington-Kirkpatrick Model

Sponsor(s):
Statistical Science

Friday, October 07, 2022

3:30 pm - 4:30 pm

Mark Sellke, Assistant Professor, Dept. of Statistics, Harvard

## The Shadow Carceral State and Racial Inequality

Sponsor(s):
Statistical Science

Friday, October 14, 2022

3:30 pm - 4:30 pm

Ted Enamorado, Washington University at St Louis

## Comparison of Markov chains via weak Poincaré inequalities with application to pseudo-marginal MCMC

Sponsor(s):
Statistical Science

Friday, October 21, 2022

3:30 pm - 4:30 pm

Andi Wang, Senior Research Associate, School of Mathematics Research, University of Bristol-Warwick

## Scalable community detection in massive networks via predictive inference

Sponsor(s):
Statistical Science

Friday, October 28, 2022

3:30 pm - 4:30 pm

Srijan Sengupta, Assistant Professor, NC State University

## Disentangling confounding and nonsense associations due to dependence

Sponsor(s):
Statistical Science

Friday, November 04, 2022

3:30 pm - 4:30 pm

Elizabeth Ogburn, Associate Professor, Johns Hopkins University

## Representation Learning: A Causal Perspective

Sponsor(s):
Statistical Science

Friday, November 11, 2022

3:30 pm - 4:30 pm

Yixin Wang, Assistant Professor, Statistics, University of Michigan

## Interpretable sensitivity analysis for the Baron–Kenny approach to mediation with unmeasured confounding

Friday, November 18, 2022

3:30 pm - 4:30 pm

Peng Ding, University of California, Berkeley

## High Dimensional Random Forests Estimation and Inference

**CANCELED**

Friday, December 02, 2022

3:30 pm - 4:30 pm

Yingying Fan, Professor, USC Marshall

## Structured prior distributions for the covariance matrix in latent factor models

Sponsor(s):
Statistical Science

Friday, December 09, 2022

3:30 pm - 4:30 pm

Sarah Heaps, Associate Professor, Statistics, Durham University

## Make your own kind of sparse DAG; Fit your own special scalable Gaussian process. Bayesian geostatistics for massive data

Sponsor(s):
Statistical Science

Friday, January 13, 2023

3:30 pm - 4:30 pm

Dr. Michele Peruzzi, Postdoctoral Associate, Duke Statistical Science

## 3D Bivariate Spatial Modelling of Argo Ocean Temperature and Salinity Profiles

Sponsor(s):
Statistical Science

Wednesday, January 18, 2023

3:30 pm - 4:30 pm

Dr. Mary Salvaña, Statistician / Postdoctoral Research Fellow, University of Houston

## Hierarchical Structures in Bayesian Statistics

Sponsor(s):
Statistical Science

Friday, January 20, 2023

3:30 pm - 4:30 pm

Filippo Ascolani, PhD student, Statistics, Bocconi University,

## Identifiable Deep Generative Models via Sparse Decoding

Sponsor(s):
Statistical Science

Wednesday, January 25, 2023

3:30 pm - 4:30 pm

Dr. Gemma Moran, Postdoctoral Associate, Columbia Data Science Institute

## To Adjust or not to Adjust? Estimating the Average Treatment Effect in Randomized Experiments with Missing Covariates

Sponsor(s):
Statistical Science

Friday, January 27, 2023

3:30 pm - 4:30 pm

Dr. Anqi Zhao, Assistant Professor, National University of Singapore

## Undergrads Take Over StatSci Seminar!

Sponsor(s):
Statistical Science

Friday, February 10, 2023

3:30 pm - 4:30 pm

Statistical Science Undergraduate Students

## Harvard Business School - Information Session (MBA and 2+2 Program)

Sponsor(s):
Trinity College

Wednesday, March 01, 2023

7:00 pm - 8:30 pm