Todd Kuffner

Todd Kuffner

Associate Professor of Statistics and Data Science
PhD, Imperial College London
research interests:
  • Bayesian Asymptotics
  • Applications of Differential Geometry to Statistics
  • Empirical Likelihood
  • Variable and Model Selection Methods

contact info:

mailing address:

  • Washington University
    CB 1281
    One Brookings Drive
    St. Louis, MO 63130-4899

Professor Kuffner's research spans statistical theory, foundations, and methodology.

Using techniques from asymptotic theory, Kuffner studies the questions of validity, accuracy and power of statistical inference procedures, and also develop methods which can help achieve these goals. He is 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, he is currently working on post-selection inference, the bootstrap, and prediction after model selection.