Every summer, we invite up to two eminent statisticians/probabilists to teach a short special topic course to our Ph.D. students. These 1-2 week-long courses, allow our Ph.D. students to engage with an eminent researcher to learn and discuss advanced topics in a relaxed setting.
Summer 2024
1. Aaditya Ramdas, Professor, Carnegie Mellon University
GR8201 (001) Topics in Theoretical Statistics
Game-Theoretic Statistics and Safe Anytime-Valid Inference
2. Rina Foygel Barber, Professor, University of Chicago
GR8201 (002) Topics in Theoretical Statistics
An Introduction to Conformal Prediction and Distribution-Free Inference
Summer 2023
1. Fan Li, Professor, Department of Statistical Science, Duke University.
GR8201 (001) – Topics in Theoretical Statistics
“Causal Inference”
2. Arthur Gretton, Professor, University College London
GR8201 (002) – Topics in Theoretical Statistics
“Generative Models Using Kernel and Neural Divergence Measures”
Summer 2022
1. Richard Samworth, Professor , University of Cambridge
GR8201 – Topics in Theoretical Statistics
“Nonparametric Inference under shape constraints”
Summer 2021
1. Xihong Lin, Professor, Department of Biostatistics, Harvard University
GR8201 – Topics in Theoretical Statistics
“Scalable Statistical Inference for Big Data with Applications”
Summer 2020
1. Peter Bühlmann, Professor, ETH Zurich
Topics Course: ‘Causality — in a wide sense.’
Summer 2019
1. Tze Leung Lai, Ray Lyman Wilbur Professor of Statistics, Stanford University
GR8201D – Topics in Statistics
“The financial industry (Wall Street) and the broader economy (Main Street) undergo cycles of boom and bust.”
2. Vladimir Koltchinskii, Professor, Georgia Institute of Technology, School of Mathematics
GR8301 – Probability Theory
“Estimation of Functionals of High-Dimensional Parameters”
Summer 2018
GR8301D – Topics in Probability
“Introduction to high-dimensional probability and its applications.”
2. Liza Levina, Vijay Nair Collegiate Professor and Chair, Michigan Institute for Data Science
GR8201D – Topics in Statistics
“Statistical models and algorithms for analyzing network data.”
Summer 2017
1. Denis Talay, Professor, École Polytechnique
GR8301D – Topics in Probability
“The course is aimed to introduce the analysis of invariant measures of ergodic diffusion processes with two main motivations: the paramedic estimation of ergodic diffusions and the long time behaviour of numerical simulations.”
Summer 2016
1. Sourav Chatterjee, Professor, Stanford University
G8201 – Topics in Probability
“A short course in Stein’s method”
2. John Lafferty, Professor, The University of Chicago
G8200(1) – Topics in Statistics
“High Dimensional Statistical Learning”
Summer 2015
G8201 – Topics in Probability
“Stochastic optimization in optimal portfolio selection and pricing in incomplete markets.”
2. Tze Leung Lai, Ray Lyman Wilbur Professor of Statistics, Stanford University
GR8200D – Topics in Statistics
“Statistical Methods for Medical Product Safety Evaluation”
Summer 2014
G8200D – Topics in Statistics
“Gaussian Processes: Theory, Applications and Computation”
Summer 2013
1. Michael A. Newton, Professor, University of Wisconsin-Madison
G8200D – Topics in Statistics
“Statistical Modeling in Cancer and Molecular Biology”
Summer 2012
G8200D – Topics in Statistics
2. Mark Podolskij, Professor, Department of Mathematics, Aarhus University
G8201D – Topics in Probability
Summer 2011
1. Guido Consonni, Professor, Universita’ Cattolica del Sacro Cuore
G8200D – Topics in Statistics
“Objective Bayesian Model Choice”
2. Henry Wynn, Professor, London School of Economics
G8201D – Topics in Probability
Summer 2010
G8200D – Topics in Statistics
“Statistical Machine Learning”
2. Ioannis Kontoyiannis, Professor, Athens Univ of Economics & Business
G8201D – Topics in Probability
“Non-asymptotics: Probability, entropy and additive combinatorics”
Summer 2009
1. Andrea Buja, Professor, The Wharton School University of Pennsylvania
G8200D – Topics in Statistics
“Lectures on Statistics and Data Analysis”
2. Philip Protter, Department of Statistics, Columbia University
G8201D – Topics in Probability
“In this series of lectures we will introduce financial asset pricing theory, explain risk neutral measures and self-financing strategies, and show the fundamental role played by bubbles.”
Summer 2008
1. Bin Yu, Professor, University of California, Berkeley
G8200D – Topics in Statistics
“Information Theory and Statistics”
2. Jean Bertoin, Professor, Institut für Mathematik Universität Zürich
G8201D – Topics in Probability
“An introduction to subordinators and Levy processes”