Previous Lectures

Buehler-Martin Lectureship

Year	Speaker	Lecture Titles
2021	Hadley Wickham RStudio, Stanford University, University of Auckland Roger Peng Johns Hopkins Bloomberg School of Public Health	5/7: dplyr: One Language, Many Implementations 5/6: Reproducible Research: What Have We Learned in 20 Years?
2019	James Robins Harvard University Elizabeth Halloran University of Washington, Fred Hutchinson Cancer Research Center	5/3: On Assumption-Free Tests and Confidence Intervals for Causal Effects Estimated with Machine Learning 5/2: From Dependent Happenings to Causal Inference with Interference
2018	Douglas Nychka University Corporation for Atmospheric Research Richard Smith University of North Carolina - Chapel Hill	5/4: Large and Non-stationary Spatial Fields: Quantifying Uncertainty in Climate Models 5/4: Influence of Climate Change on Extreme Weather Events
2017	Vince Clark University of New Mexico Martin Lindquist Johns Hopkins University	5/6: Neuroimaging Combined with Neurostimulation: New Methods for Verifying and Utilizing the Causal Connections Between Brain and Behavior 5/6: Brain Signatures and Models in Translational Neuroimaging
2016	Xuming He Department of Statistics, University of Michigan	3/29: From Statistical downscaling to Multivariate Quantiles 3/31: Model-Based Inference in Subgroup Analysis
2015	Lynn Y.S. Lin Lynn Y.S. Lin Statistical Consulting, Inc.	3/25: How Did I Get Into New Product Sales Forecasting Business?
2014	Bruce Lindsday Penn State University	3/10: Mixture models: the data story, the mysteries, and the surprises 3/12: Sufficient projections through a Fisherian information matrix
2013	Michael Newton University of Wisconsin, Madison	3/26: Why Don't We Agree? Studying Influenza with RNA Interference 3/27: Decoding Functional Signals with the Role Model 3/28: Probabilities Over Ranks of Gamma or Normal Random Variables
2011 (Fall)	Adrian Raftery Professor of Statistics and Sociology, University of Washington	10/25: Fast Inference for Model-Based Clustering of Networks Using an Approximate Case-Control Likelihood 10/26: Probabilistic Projection of Life Expectancy for All Countries to 2100 10/27: Probabilistic Weather Forecasting Using Ensemble Bayesian Model Averaging
2011 (Spring)	Jianqing Fan Princeton University	4/19: A Statistician's Guide to Vast-dimensional Space 4/20: Refitted Cross-validation in Ultrahigh Dimensional Regression 4/21: Control of the False Discovery Rate Under Arbitrary Covariance Dependence
2010	John Rice University of California at Berkeley	4/12: Measuring Traffic 4/14: Statistics of the Taiwanese-American Occultation Survey 4/15: Searching for Gamma-Ray Pulsars: Detecting Periodicity in a Point Process
2009	Trevor Hastie Stanford University	3/9: Modern Trends in Data Mining 3/10: Regularization Paths and Coordinate Descent (joint work with Jerome Friedman and Rob Tibshirani)
2008	Lawrence D. Brown Wharton School University of Pennsylvania	4/29: In-Season Prediction of Batting Averages: A Field-test of Basic Empirical Bayes and Bayes Methodologies 4/30: Non-parametric Empirical Bayes and Compound Bayes Estimation of Independent Normal Means 5/1: A Root-Unroot Algorithm for Nonparametric Density Estimation and an Implementation via Adaptive Wavelet Block Thresholding
2007	Michael Titteringten University of Glasgow, Scotland, UK	4/10: Pearson the Elder - A Statistical Giant 4/11: Variational approximations in incomplete-data problems 4/12: Bayesian measures of complexity, and model selection, based on incomplete data
2006	Peter McCullagh University of Chicago	3/20: Some Remarks About Spatial Correlation of Crop Yields 3/22: Partition Models and Cluster Processes 3/23: Random Partitions and Logistic Classification
2005	Raymond J. Carroll Texas A & M	3/29: Measuring Diet: Is it Possible? 3/30: Longitudinal and Clustered Data and Non/Semiparametric Regression 3/31: Semiparametric Methods for Gene-environment Case-control Studies When Gene and Environment Are Independent in the Population
2004	Elizabeth Thompson University of Washington	4/19: Inferring Relationships Among Populations and Individuals 4/20: The Structure of Pedigree Data and the Detection of Linkage 4/22: Monte Carlo Likelihood in Genetic Mapping
2003	Peter Hall Australian National University	4/29: Nonparametric Methods for Estimating Light Curves for Periodic Variable Stars 4/30: Statistical Inference in High-Dimensional, Low Sample Size Settings 5/1: Testing for Equality of Distributions in Very High Dimensions
2001	David Freedman University of California	4/16: Statistical Issues in Census 2000 4/17: The Swine Flu Vaccine and Guillain-Barre syndrome 4/19: Salt and Blood Pressure: Conventional Wisdom Reconsidered
1999 (Fall)	Bradley Efron Stanford University
1999 (Spring)	James O. Berger Duke University
1998	John Hartigan Yale University
1997	Grace Wahba University of Wisconsin
1994	Anthony Atkinson London School of Economics, UK
1993	John Aitchison University of Virginia
1992	A.W.F. Edwards University of Cambridge, UK

Seymour Geisser Distinguished Lectures

Year	Speaker	Title
2023	James Hodges University of Minnesota	Provocative Observations About the Foundations of Statistics
2022	Francesca Chiaromonte Penn State University	In Awe of Today's Data: Reducing, Selecting, Leveraging Structures- and Looking Ahead
2018	Steven MacEachern Ohio State University	A Brief Tour of Bayesian Nonparametrics
2017	Merlise A. Clyde Duke University	Bayesian Model Choice: Past, Present, Future
2016	Rob Weiss Department of Biostatistics, UCLA Fielding School of Public Health	Analysis of Hierarchical Sexual Behavior Profiles over Time
2015	Ron Christensen University of New Mexico	Another look at the lasso
2014	Joseph Ibrahim University of North Carolina at Chapel Hill	Likelihood-based Methods for Missing Data and Bayesian Model Assessment
2013	Rob McCulloch University of Chicago	The volatility of financial instruments centered on the tools of predictivism
2012	Ed George Wharton School, University of Pennsylvania	EMVS: The EM Approach to Bayesian Variable Selection
2012	Jeff Rosenthal University of Toronto	Adapting Metropolis Algorithms and Gibbs Samplers
2010	Wesley Johnson University of California, Irvine	On the Value of Incorporating Scientific Input in Modeling and Data Analysis and How to Do It Without Pain
2009	Jayanta Ghosh Purdue University	Two Groups and One Group Models for Multiple Tests for Microarrays and Other Examples...a Survey and New Results
2008	Malay Ghosh University of Florida	Objective Priors: a selective review
2007	Teddy Seidenfeld Carnegie Mellon University	Conditional Independence, Imprecise Probabilities, Null-Events, and Graph-Theoretic Models
2006	Philip Dawid University College London	Interpreting DNA profile evidence in complex disputed paternity cases: Bayesian networks to the rescue (Joint work with Julia Mortera and Paola Vicard, Universitá Roma Tre)
2005	James O. Berger Duke University	Something Old and Something New: Bivariate Normal and Computer Models