Recent Summer Topic Courses

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 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

1. Roman Vershynin, Professor of Mathematics, University of California, Irvine and Associate Director of the Center for Algorithms, Combinatorics and Optimization

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

1. Thaleia Zariphopailou, Professor, Department of Mathematics, College of Natural Sciences Department of Information, Risk, and Operations Management, University of Texas at Austin

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

1. Michael Stein, Ralph and Mary Otis Isham Professor, Department of Statistics and the College, University of Chicago

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

1. Mark Hansen, David and Helen Gurley Brown Professor of Journalism and Innovation; Director, David and Helen Gurley Brown Institute of Media Innovation, Columbia School of Journalism

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

1. Larry Wasserman, Professor, Department of Statistics and in the Machine Learning Department , Carnegie Mellon University

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”