Todd Kuffner
Home
Research
Events
Students
Teaching
Other















News and Upcoming Events:

May 6-8, 2020
Program Committee and Organizer of 3 Sessions
7th Bayes, Fiducial and Frequentist Statistics Conference (BFF7)
Fields Institute, Toronto

June 21-23, 2020
Lead Organizer
WHOA-PSI 5
St. Louis, Missouri
WUSTL

June 25-28, 2020
Lead Organizer
Open Problems in Parametric Likelihood-Based Inference
St. Louis, Missouri
WUSTL


Recent & Upcoming Talks:

March 8 - 13, 2020
The Interface Between Selective Inference and Machine Learning
Organizers: Rina Foygel Barber, Will Fithian and Daniel Yekutieli
Banff International Research Station
Banff, Canada

October 21, 2019
Colloquium
Dept. of Statistics
Harvard University

Jul 27 - Aug 1, 2019
Joint Statistical Meetings
Invited Session (Organizer: Rob Tibshirani).
Denver, Colorado

April 15, 2019
Colloquium
Dept. of Statistics
Indiana University

Nov 30 - Dec 1, 2018
Workshop in Honor of Lawrence D. Brown
Invited Speaker.
University of Pennsylvania

September 25-26, 2018
Statistical Inference, Learning and Models in Data Science
Invited Session (Organizer: Nancy Reid).
Fields Institute, Toronto



I am an associate professor in the Department of Mathematics and Statistics at Washington University in St. Louis.

Research interests:

  • Philosophy of statistics, and philosophy of data science
  • Higher-order asymptotic theory for statistical inference (Bayesian and frequentist)
  • Bootstrap theory and methodology for dependent data, and for big data
  • Post-selection inference and post-selection prediction
  • Bayesian-Fiducial-Fisherian-Frequentist reconciliation
  • Methodology for neuroscience, high-energy physics, and environmental science

My research spans statistical theory, foundations, and methodology. Using techniques from asymptotic theory, I study the questions of validity, accuracy and power of statistical inference procedures, and also develop methods which can help achieve these goals. I am interested in the relationships between different paradigms for statistical inference, such as neo-Fisherian, Bayesian, and frequentist approaches, and also new methods for data-driven science from machine learning. In addition to ongoing work on higher-order asymptotics for likelihood-based and Bayesian inference, I am currently working on post-selection inference, the bootstrap, and prediction after model selection. I received my PhD in mathematics from Imperial College London under the direction of Alastair Young.

I am the lead organizer of the Workshop on Higher-Order Asymptotics and Post-Selection Inference (WHOA-PSI), which is taking place for the fifth time from June 21-23, 2020.

Education
Ph.D. Mathematics, Imperial College London
M.Sc. Econometrics and Mathematical Economics, London School of Economics
M.Sc. Economics, London School of Economics
B.A. Economics, University of Michigan Ann Arbor

I am an Associate Editor at the following journals:
Harvard Data Science Review, 2018- (inaugural Editorial Board)
Sankhya Series A, 2019-
Journal of the American Statistical Association - Theory & Methods, 2020-


Washington University:
Department of Mathematics and Statistics
1 Brookings Drive, Campus Box 1146
St. Louis, MO 63130

E-mail: kuffner@wustl.edu

Recent & Upcoming Visitors:

February 5-7, 2020
Ian McKeague
Columbia University

November 14-15, 2019
Naveen Narisetty
University of Illinois Urbana-Champaign

November 7-8, 2019
Andrew Womack
Indiana University

May 9-10, 2019
Andreas Buja
University of Pennsylvania

April 19, 2019
Haochang Shou
University of Pennsylvania

April 12, 2019
Ruobin Gong
Rutgers University

March 22, 2019
Konstantin Genin
University of Toronto

Feb. 22, 2019
Chaitra Nagaraja
Fordham University

Sep. 26-27, 2018
David Banks
SAMSI and Duke University