Some presentations

• SIPTA Summer School 2026
  Statistics, imprecise probabilities, and possibilistic inferential models [slides]
  LMU Munich, Germany, July 2026

• JMP Research Seminar
  Possibilistic inferential models, properties, and Monte Carlo computations [slides]
  Cary, NC, June 2026

• Brin Mathematical Research Center Workshop
  Imprecision is imperative for reliable uncertainty quantification [slides]
  University of Maryland, February 2026

• EurIPS Workshop
  Imprecision is imperative for reliable uncertainty quantification
  Copenhagen, Denmark, December 2025

• O'Bayes Workshop
  O'Bayes reIMagined: probabilistic approximations of possibilistic inferential models [slides]
  Athens, Greece, June 2025

• PostBayes Seminar Series
  Learning rate selection for Gibbs posterior distributions [slides] [youtube]
  Virtual, March 2025

• Department of Statistics Seminar
  Imprecise probability in statistical inference: why, what, where, and how [slides]
  University of Pittsburgh, February 2025.

• Department of Statistics Seminar
  Regularized e-processes: anytime-valid inference with knowledge-based efficiency gains [slides]
  University of Florida, October 2024.

• 8th International Conference on Belief Functions
  --Variational approximations of possibilistic inferential models [slides]
  --Which statistical hypotheses are afflicted with false confidence? [slides]
  Ulster University, Belfast, UK, September 2024.

• Finnish Statistical Society's Statistical Days 2024
  Imprecise probability in statistical inference: why, where, and how [slides]
  University of Aalto, Finland, June 2024.

• Finnish Doctoral Education Network in Stochastics & Statistics — Five-day intensive course
  Topics in Statistical Inference [slides]
  Lammi Biological Research Station, Finland, May 2024.

• Oberwolfach Workshop on Game-theoretic Statistical Inference, etc.
  Safe & reliable possibilistic e-UQ [slides]
  Oberwolfach, Germany, May 2024.

• Department of Statistics Seminar
  Imprecise probability in statistical inference: why, what, where, and how [slides]
  University of Missouri, April 2024.

• Royal Statistical Society Discussion Meeting
  (Seconder of the vote of thanks and) Discussion of Grunwald et al's paper "Safe Testing" [slides]
  London, January 2024.

• 6th Belief Functions Theory and Applications School
  Old and new developments in consonant belief functions for statistical inference [slides]
  Japan Advanced Institute of Science & Technology, October 2023.

• Department of Statistics Seminar
  Imprecise probability in statistical inference: why, what, where, and how [slides]
  North Carolina State University, October 2023.

• SIPTA Seminar
  Fisher's underworld and the behavioral--statistical reliability balance in scientific inference [slides] [youtube]
  Online, October 2023.

• Stanford's International Seminar on Selective Inference
  Discussion of Min-ge Xie's "Repro samples method..." [min-ge's paper] [my slides]
  Virtual, June 2023.

• 10th International Purdue Statistics Symposium
  --Tutorial on Inferential Models [slides]
  --Imprecision in inferential models: why, what, and how [slides]
  Purdue University, June 2023.

• Bayes, Fiducial, and Frequentist Workshop: BFF8
  Valid and efficient possibilistic inference in machine learning problems [slides]
  University of Cincinatti, May 2023.

• Department of Mathematical Sciences Colloquium
  A possibility-theoretic solution to the Bayesian-versus-frequentist predicament [slides]
  University of Texas at Dallas, April 2023.

• BELIEF 2022
  A practical strategy for valid partial prior-dependent possibilistic inference [slides]
  Paris (online for me), October 2022.

• Conference on Advances in Data Science
  All Bayesian inference is approximate [slides]
  Texas A&M University, October 2022.

• 2022 Joint Statistical Meetings
  Leveraging low-dimensional structure for efficient Gibbs posterior inference [slides]
  Washington DC, August 2022.

• 6th International Webinar on Recent Trends in Statistical Theory and Applications
  Valid and efficient possibilistic inference across a spectrum of partial prior information [slides]
  Special session in honor of Professor J. K. Ghosh
  University of Kerala, India, June 2022.

• Econometrics and Statistics (EcoSta) 2022
  Gibbs posterior distributions: Construction, concentration, and calibration [slides]
  Ryukoku University, Kyoto, Japan, June 2022.

• Bayes, Fiducial, and Frequentist Workshop: BFF7
  Valid and efficient possibilistic inference across a spectrum of partial prior information [slides]
  University of Toronto, May 2022.

• Foundations of Probability Seminar
  Cournot's principle and Lewis's best-system interpretation [slides]
  Rutgers University, 2022.

• Algorithms & Computationally Intensive Inference Seminar
  Data-driven calibration of generalized posteriors [slides]
  University of Warwick, UK, 2022.

• CMStatistics 2021
  False confidence, imprecise probability, and valid statistical inference [slides]
  London, UK, December 2021.

• Statistics Seminar
  Generalized inferential models: basics and beyond [slides]
  Northwestern Polytechnical University, China, November 2021.

• Statistics Power Half-Hour
  Checking model assumptions: Why, how, and will it hurt? [slides]
  NCSU Library, October 2021.

• Van Dantzig Seminar
  Imprecise probability and valid statistical inference [slides]
  The Netherlands, April 2021.

• Statistics Seminar
  Imprecise probability and valid statistical inference [slides]
  North Carolina State University, April 2021.

• Theoretical and Applied Data Science Seminar
  Valid inferential models and conformal prediction [slides]
  Iowa State University, March 2021.

• Machine Learning Seminar
  Valid inferential models and conformal prediction [slides]
  Purdue University, March 2021.

• Statistics Power Half-Hour
  Statistical Reasoning 101 [slides]
  NCSU Library, March 2021.

• BFF 6.5 -- Workshop on Bayesian, Fiducial, and Frequentist Inference
  Imprecise probability in frequentist inference [slides]
  Researchers.One, February 2021.

• SIPTA School 2020/2021
  Inferential Models (short course) [slides]
  Institute for Risk and Uncertainty, University of Liverpool, UK, January 2021.

• Department of Data Science and Operations Seminar
  Empirical priors for inference on high-dimensional structured parameters. [slides]
  University of Southern California, October 2020.

• Joint Statistical Meetings
  Empirical priors for inference on high-dimensional structured parameters.
  Virtual, August 2020.

• BayesComp 2020
  Gibbs posterior distributions. [slides]
  University of Florida, January 2020.

• ISIPTA 2019
  --On valid uncertainty quantification about a model. [slides] [poster]
  --Possibility measures for valid statistical inference based on censored data. [slides]
  --Incorporating expert opinion in an inferential model while maintaining validity. [slides]
  Ghent University, Belgium, July 2019.

• O'Bayes 2019
  Objective data-dependent distributions. [slides]
  University of Warwick, UK, June 2019.

• 6th African International Conference on Statistics
  --False confidence, non-additive beliefs, and valid statistical inference. [slides]
  --Construction, concentration, and calibration of Gibbs posteriors. [slides]
  Arsi University, Ethiopia, May 2019.

• Applied and Computational Mathematics and Statistics Department Colloquium
  False confidence, non-additive beliefs, and valid statistical inference. [slides]
  University of Notre Dame, February 2019.

• BELIEF 2018/SMPS 2018
  Belief functions and valid statistical inference (keynote).
  Compiegne, France, September 2018.

• 2018 IMS Annual Meeting
  Construction, concentration, and calibration of Gibbs posteriors.
  (Also presented in the session on open-access e-journals [slides])
  Vilnius, Lithuania, July 2018.

• 2018 ISBA World Meeting
  Empirical priors for wranglin' with structured high-dimensional problems.
  (Editor's choice session: "Lassos and horseshoes for the sparse Bayesian cowboy")
  Edinburgh, Scotland, June 2018.

• 2018 IISA International Conference on Statistics
  Fast nonparametric estimation of a smooth mixing density.
  (Memorial session for Professor J.K. Ghosh)
  University of Florida, May 2018.

• 5th Bayesian, Fiducial, and Frequentist Conference
  Probability dilution, false confidence, and non-additive beliefs.
  University of Michigan, May 2018.

• 12th UMBC Probability and Statistics Day
  Fast nonparametric estimation of a smooth mixing density.
  (Keynote/Memorial session for Professor J.K. Ghosh)
  University of Maryland Baltimore County, April 2018.

• Foundations of Probability Seminar
  Probability dilution, false confidence, and non-additive beliefs.
  Rutgers University, April 2018.

• CMStatistics 2017
  Posterior concentration rates via empirical priors.
  London, UK, December 2017.

• 2nd Workshop on Higher-Order Asymptotics & Post-Selection Inference
  On valid post-selection prediction in regression.
  Washington University in St. Louis, August 2017.

• 11th Conference on Bayesian Nonparametrics
  Model misspecification on purpose.
  Paris, France, June 2017.

• 4th Bayesian, Fiducial, and Frequentist Conference
  Confidence, probability, and plausibility.
  (Also presented in the "Views from Rising Stars" panel discussion)
  Harvard University, May 2017.

• Laber Labs Workshop
  A not-so-short introduction to stochastic approximation theory and applications. [slides]
  North Carolina State University, 04/2017.

• 10th International Conference of the Thailand Econometric Society
  Valid prior-free probabilistic inference.
  (Plenary Session invited talk)
  Chiang Mai University, Thailand, January 2017.

• Department of Statistics Seminar
  Posterior inference without (really) using Bayes. [slides]
  North Carolina State University, December 2016.

• Latent Variables Conference
  A double empirical Bayes approach for high-dimensional problems.
  University of South Carolina, October 2016.

• Workshop on Fusion Learning, BFF inferences and Statistical Foundations
  Beliefs, validity, and the foundations of statistics.
  Rutgers University, April 2016.

• Department of Statistics Colloquium
  Inferential models: a framework for prior-free probabilistic inference.
  North Carolina State University, November 2015.

• Statistics Colloquium
  High-dimensional posterior inference via double empirical Bayes.
  Texas A&M University, February 2015.

• International Conference on Advances in Interdisciplinary Statistics and Combinatorics
  Empirical Bayes posterior concentration in sparse high-dimensional linear models,
  Greensboro, NC, October 2014.

• Department of Statistics Seminar
  Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector.
  University of Illinois at Urbana–Champaign, September 2013.

• Department of Statistics Seminar
  A Bayesian test of normality versus a Dirichlet process mixture alternative.
  Northwestern University, January 2013.

• Statistical Science Seminar
  Inferential models: A framework for prior-free posterior probabilistic inference.
  Duke University, November 2012.

• ASA Northeastern Illinois Chapter Meeting
  A nonparametric empirical Bayes framework for large-scale multiple testing.
  Northbrook, IL, October 2012.

• Statistics and Probability Seminar
  Plausibility functions and exact frequentist inference.
  Michigan State University, October 2012.

• Purdue Symposium on Statistics
  Inferential models: A framework for prior-free posterior probabilistic inference.
  Purdue University, June 2012.

• ACMS Department Colloquium
  Predictive recursion marginal likelihood and application to large-scale simultaneous testing.
  University of Notre Dame, January 2011.