Bahadur Memorial Lectures

In honor of Raj Bahadur's fundamental contributions to statistics and to our department.

R.R. Bahadur's Lectures on the Theory of Estimation
By Raghu Raj Bahadur, Stephen M. Stigler,
Wing Hung Wong, and Daming Xu

LECTURE 22:  May 1 and 4, 2023

SARA VAN DE GEER, Department of Mathematics, Seminar für Statistik (SfS), ETH Zürich
"Logistic regression with small Bayes error"
"Small noise, no regularization"

LECTURE 21 : April 7, 2022 

MICHAEL A. NEWTON, Department of Statistics, University of  Wisconsin
"Can clustering improve the performance of large-scale hypothesis testing?  Ideas from an empirical Bayes lab"

LECTURE 20 : May 6 and 9, 2019

IAIN JOHNSTONE, Departments of Statistics, Health Research and Policy, Stanford University
"High Dimensional Classical Multivariate Analysis: Ladders and Local Asymptotic Normality"
"High Dimensional Principal Component Analysis: Biases and Balms."

LECTURE 19: April 16 and 19, 2018

HÅVARD RUE, Departments of Statistics and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology
"Some New Developments in the R-INLA Project"
"Penalizing Model Component Complexity: A Principled Practical Approach to Constructing Priors"

LECTURE 18: April 19 and 20, 2017

XIAO-LI MENG, Department of Statistics, Harvard University
"There is Individualized Treatment. Why Not Individualized Inference?"
"From Eckhart Hall to (almost) White House:  An Unexpected Statistical Journey (Or:  How small are my big data?)"

LECTURE 17: May 11 and 13, 2016

DONALD GEMAN, Department of Applied Mathematics and Statistics, Johns Hopkins University
"Designing Vision Machines by Entropy Pursuit"
"Testing Vision Machines by Entropy Pursuit"

LECTURE 16: May 4 and 7, 2015

MICHAEL I. JORDAN, Department of Statistics, University of California, Berkeley
"Distributed Computing, the Bootstrap, and Concurrency Control"
"On Computational Thinking, Inferential Thinking, and 'Big Data'"

LECTURE 15: April 2 and 3, 2014

SUSAN A. MURPHY, Department of Statistics, University of Michigan, Ann Arbor
"Machine Learning Methods for Individualizing Just in Time Adaptive Interventions"
"Getting SMART about Adapting Interventions"

LECTURE 14:  April 15 and 18, 2013

PETER J. GREEN, University of Bristol and University of Technology, Sydney
"Emission Tomography and Bayesian Inverse Problems"
"Bayesian Graphical Model Determination"

LECTURE 13:  April 16 and 17, 2012

PETER BÜHLMANN, Seminar für Statistik, ETH Zürich
"Assigning Statistical Significance in High-Dimensional Problems"
"Causal Statistical Inference and Intervention Experiments for Large-Scale Biological Systems"

LECTURE 12:  April 11 and 14, 2011

JAMES O. BERGER, Department of Statistical Science, Duke University
"Bayesian Adjustment for Multiplicity"
"I don't know where I'm gonna go when the volcano blows"

LECTURE 11:   November 9 and 12, 2009

PETER HALL, Department of Mathematics and Statistics, University of Melbourne, Australia
"Modelling the Variability of Rankings"
"Contemporary Frontiers in Statistics"

LECTURE 10:  May 18 and 21, 2009

STEFFEN L. LAURITZEN, Department of Statistics, University of Oxford
"Sufficiency and Transitivity"
"Bayesian Networks for the Analysis of DNA Mixtures"

LECTURE 9:  May 5 and 8, 2008

STUART GEMAN, Division of Applied Mathematics, Brown University
"Rare Events in the Financial Markets"
"On the Peculiar Statistics of Natural Images"

LECTURE 8:  March 26 and 29, 2007

WING H. WONG, Department of Statistics, Stanford University
"Statistical Issues in the Study of Gene Regulation"
"Learning Causal Bayesian Network Structures from Experimental Observations"

LECTURE 7:  May 8 and 11, 2006

ELIZABETH A. THOMPSON, Departments of Statistics, and of Genome Sciences, University of Washington
"Monte Carlo Likelihood Inference in Latent Variable Problems"
"Uncertainty and Evidence in the Face of Unseen Data"

LECTURE 6:  May 16 and 18, 2005

WILLEM R. VAN ZWET, Mathematical Institute, University of Leiden
"Statistics and the Law: The Case of the Negligent Nurse"
"Kakutani’s Interval Splitting Scheme"

LECTURE 5:  October 16 and 17, 2003

DAVID O. SIEGMUND, Department of Statistics, Stanford University
"Statistical Problems of Genetic Mapping"
"Gene Mapping and Model Selection"

LECTURE 4:  May 17 and 20, 2002

ADRIAN BADDELEY, Department of Mathematics and Statistics, University of Western Australia
"Counting Leaves on a Tree and Neurons in the Brain"
"Practical Maximum Pseudolikelihood for Spatial Data"

LECTURE 3:  May 8 and 9, 2001

PETER J. BICKEL, Department of Statistics, University of California, Berkeley
"Suggestive Statistics and Texture Analysis"
"Testing Semiparametric Hypotheses and Unorthodox Bootstraps"

LECTURE 2:  May 23 and 24, 2000

PERSI DIACONIS, Department of Statistics, Stanford University
"On Coincidences"

LECTURE 1:  June 1 and 3, 1999

LAWRENCE D. BROWN, Department of Statistics, University of Pennsylvania
"Current Plans and Prospects for Census 2000"
"New, Improved Confidence Intervals for a Binomial Proportion"