معرفی
Todd Kuffner is an Associate Professor in the Department of Mathematics and Statistics at Washington University in St. Louis, within the College of Arts & Sciences. His research focuses on statistical theory, foundations, and methodology, particularly Bayesian asymptotics, higher-order asymptotics, post-selection inference, and bootstrap methods. He holds a PhD in Mathematics from Imperial College London and has organized major workshops like WHOA-PSI and BFF conferences.
Education: PhD in Mathematics (Imperial College London), M.Sc. in Econometrics and Mathematical Economics (London School of Economics), M.Sc. in Economics (London School of Economics), B.A. in Economics (University of Michigan).
Research Interests: Kuffner explores validity, accuracy, and power of statistical inference procedures, with a focus on neo-Fisherian, Bayesian, and frequentist paradigms. Current projects include post-selection inference, bootstrap methods, and prediction after model selection. He actively engages in interdisciplinary applications across neuroscience, environmental science, and high-energy physics.
Grants & Advising: Principal Investigator on NSF grants including DMS-1811936 (2018-2021) and DMS-1812088 (2018). Advised PhD students like Qi Wang and Qiyiwen Zhang. Organized over 20 conferences/workshops, including the 5th WHOA-PSI in 2020.
Labs/Teams: Leads the Workshop on Higher-Order Asymptotics and Post-Selection Inference (WHOA-PSI), co-edits journals like Harvard Data Science Review and Journal of the American Statistical Association. Hosted numerous visiting scholars and collaborators.
