## Bayesian Approaches for Dynamic Model Selection: two contributions

Sponsor(s):
Statistical Science

Friday, October 27, 2017

3:30 pm - 4:30 pm

Michele Guindani, University of California, Irvine

## An MCMC Approach to Empirical Bayes Inference and Bayesian Sensitivity Analysis via Empirical Processes

Sponsor(s):
Statistical Science

Friday, November 03, 2017

3:30 pm - 4:30 pm

Hani Doss, University of Florida

## Meta-Analysis With Multiple Imputation: Constructing Data Banks for Hard-To-Study Populations

Sponsor(s):
Statistical Science

Friday, November 10, 2017

3:30 pm - 4:30 pm

Elly Kaizar, Ohio State

## Statistical Concepts for Single-Cell Genomics

Sponsor(s):
Statistical Science

Friday, November 17, 2017

3:30 pm - 4:30 pm

Lior Pachter, Cal Tech

## Teaching to Learn: Statistics in Data Science

Sponsor(s):
Statistical Science

Monday, November 27, 2017

2:00 pm - 3:00 pm

David Dalpiaz, University of Illinois

## Anchored Bayesian Mixture Models

Sponsor(s):
Statistical Science

Wednesday, November 29, 2017

3:30 pm - 4:30 pm

Deborah Kunkel, The Ohio State University

## Approximate MCMC in Theory and Practice

Sponsor(s):
Statistical Science

Friday, December 01, 2017

3:30 pm - 4:30 pm

James Johndrow, Stanford University

## A Bayesian Approach to Interpreting Latent Fingerprint Evidence

Sponsor(s):
Statistical Science

Wednesday, December 06, 2017

3:30 pm - 4:30 pm

Maria Tackett, University of Virginia

## Estimation of open populations from multiple structurally different data sets

Sponsor(s):
Statistical Science

Friday, December 08, 2017

3:30 pm - 4:30 pm

Lutz Gruber, University of Nebraska-Lincoln

## High Dimensional Inference: Semiparametrics, Counterfactuals, and Heterogeneity

Sponsor(s):
Statistical Science

Friday, January 12, 2018

3:30 pm - 4:30 pm

Ying Zhu, Michigan State University

## Eigenvalues in multivariate random effects models

Sponsor(s):
Statistical Science

Wednesday, January 17, 2018

3:30 pm - 4:30 pm

Zhou Fan, Stanford

## Enabling likelihood-based inference for complex and dependent

Sponsor(s):
Statistical Science

Friday, January 19, 2018

3:30 pm - 4:30 pm

Jason Xu, UCLA

## Least squares estimation: beyond Gaussian regression models

Sponsor(s):
Statistical Science

Wednesday, January 24, 2018

3:30 pm - 4:30 pm

Roy Han, Univ. of Washington

## Beyond matrices: theory, methods, and applications of higher-order tensors

Sponsor(s):
Statistical Science

Friday, January 26, 2018

3:30 pm - 4:30 pm

Miaoyan Wang, UC Berkeley

## Interactive algorithms for multiple hypothesis testing

Sponsor(s):
Statistical Science

Friday, February 02, 2018

3:30 pm - 4:30 pm

Aaditya Ramdas, UC Berkeley

## Estimation and testing for two-stage experiments in the presence of interference

Sponsor(s):
Statistical Science

Wednesday, February 07, 2018

3:30 pm - 4:30 pm

Guillaume Basse, Harvard

## Constrained low-rank matrix (and tensor) estimation

Sponsor(s):
Statistical Science

Friday, February 23, 2018

3:30 pm - 4:30 pm

Lenka Zdeborova, CNRS and CEA Saclay, France, Currently at Duke for Spring Semester 2018

## Information theory and high-dimensional statistical inference

Sponsor(s):
Statistical Science

Friday, March 23, 2018

3:30 pm - 4:30 pm

Galen Reeves, Duke University

## Space-Time Modeling of Small Area Data in a Developing World Setting

Sponsor(s):
Statistical Science

Friday, March 30, 2018

3:30 pm - 4:30 pm

Jon Wakefield, University of Washington

## Incorporating Uncertainty within Human-in-the-Loop Analytics for Data Exploration

Sponsor(s):
Statistical Science

Friday, April 06, 2018

3:30 pm - 4:30 pm

Leanna House, Virginia Tech

## Manifold Data Analysis with Applications to High-Resolution 3D Imaging

Sponsor(s):
Statistical Science

Friday, April 13, 2018

3:30 pm - 4:30 pm

Matthew Reimherr, Penn State University

## Space and circular time log Gaussian Cox processes with application to crime event data

Sponsor(s):
Statistical Science

Friday, April 20, 2018

3:30 pm - 4:30 pm

Alan Gelfand, Duke University

## Introducing the overlap weights for causal inference

Sponsor(s):
Statistical Science

Friday, August 31, 2018

3:30 pm - 4:30 pm

Fan Li, Duke University Statistical Science

## On the Pitman-Yor process with spike and slab base measure

Sponsor(s):
Statistical Science

Friday, September 07, 2018

3:30 pm - 4:30 pm

Antonio Canale, University of Padova, Department of Statistical Sciences

## Bayesian Multiple Breakpoint Detection: Mixing Documented and Undocumented Changepoints

Sponsor(s):
Statistical Science

Friday, September 14, 2018

3:30 pm - 4:30 pm

Robert Lund, Clemson University, Mathematical Sciences

## Permutation tests in the presence of confounders

Sponsor(s):
Statistical Science

Friday, September 21, 2018

3:30 pm - 4:30 pm

Rina Foygel Barber, University of Chicago

## Inference of biological networks with biophysically motivated methods

Sponsor(s):
Statistical Science

Friday, September 28, 2018

3:30 pm - 4:30 pm

Rich Bonneau, New York University

## Transfer Learning and Data Alignment in Single Cell Transcriptomics

Sponsor(s):
Statistical Science

Friday, October 12, 2018

3:30 pm - 4:30 pm

Nancy Zhang, Wharton School, University of Pennsylvania

## Stochastic process models for animal trajectories

Sponsor(s):
Statistical Science

Friday, October 19, 2018

3:30 pm - 4:30 pm

Mevin Hooten, Colorado State University

## The Blessings of Multiple Causes

Sponsor(s):
Statistical Science

Friday, October 26, 2018

3:30 pm - 4:30 pm

Dave Blei, Columbia University

## The Little CpG Site That Could (and eight others less so): Developing Effect Size Measures for Mediation Analysis

Sponsor(s):
Statistical Science

Friday, November 02, 2018

3:30 pm - 4:30 pm

Yue Jiang, UNC Department of Biostatistics

## Handling Missing Data in Surveys

Sponsor(s):
Statistical Science

Monday, November 05, 2018

3:30 pm - 4:30 pm

Olanrewaju Michael Akande, Department of Statistical Science, Duke University

## Monte Carlo Methods and Contingency Tables

Sponsor(s):
Statistical Science

Friday, November 09, 2018

3:30 pm - 4:30 pm

Robert Eisinger, Instructor of Mathematics, Statistics, and Computer Science, St. Olaf College

## Using Item Response Theory to Better Understand Forensic Fingerprint Examination

Sponsor(s):
Statistical Science

Monday, November 12, 2018

3:30 pm - 4:30 pm

Amanda Luby, PhD candidate, Carnegie Mellon University.

## Web Scraping in the Statistics Curricula: Challenges and Opportunities

Sponsor(s):
Statistical Science

Wednesday, November 14, 2018

3:30 pm - 4:30 pm

Mine Dogucu, Visiting Professor, Denson University

## Design and analysis of pragmatic clinical trials to optimize clinical outcomes

Sponsor(s):
Statistical Science

Friday, November 16, 2018

3:30 pm - 4:30 pm

Hayley Belli, Post-Doctoral Fellow, Division of Biostatistics New York University Langone School of Medicine

## Covariance change point detection and identification (See abstract for full title)

Sponsor(s):
Statistical Science

Monday, November 19, 2018

3:30 pm - 4:30 pm

Shawn Santo, Ph.D. Candidate at Michigan State University

## Statistical inference for infectious disease modeling

Sponsor(s):
Statistical Science

Wednesday, January 16, 2019

3:30 pm - 4:30 pm

Po-Ling Loh, University of Wisconsin - Madison

## Support points - a new way to reduce big and high-dimensional data

Sponsor(s):
Statistical Science

Friday, January 18, 2019

3:30 pm - 4:30 pm

Simon Tsz Fung Mak, Georgia Tech

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