Distinguished Lecture Series in Statistical Sciences​

School of Industrial and Systems Engineering, Georgia Institute of Technology

1. Sep 28: Navier-Stokes, spatial-temporal kriging and combustion stability: a prominent example of physics-based analytics
2. cmenet: a new method for bi-level variable selection of conditional main effects

Department of Electrical Engineering and Computer Science and Department of Statistics, University of California, Berkeley

1. Inference Meets Computation: Dynamical, Stochastic and Economic Perspectives
2. On Gradient-Based Optimization: Accelerated, Stochastic and Nonconvex

Department of Statistics, Harvard University

Oct 29: Improving Health Mobile Interventions

Oct 30: Challenges in Developing Learning Algorithms to Personalize Treatment in Real Time

Department of Statistics, Texas A&M University

School of Mathematical and Physical Sciences, University of Technology
Sydney, Australia

1. Oct 4: A Personal Tour: The Complex Nature of Nutrient and Food Intakes, and the Effects this Complexity has on Understanding Dietary Distributions and Their Effects on Mortality and Chronic Disease
2. Oct 5: Semiparametric Analysis of Complex Polygenic Gene-Environment Interactions in Case-Control Studies

Department of Statistics, Harvard University

1. Nov 23: Essential Concepts for Causal Inference in Randomized Experiments and Observational Studies
2. Models for Imputing Missing Data, Including Methods for Assessing Sensitivity of Conclusions to Them

University of California, Berkeley

1. Apr 3: Stability
2. Apr 24: The multi-facets of a data science project to answer: how are organs formed?

Walter & Eliza Hall Institute of Medical Research, Melbourne

1. Apr 9: Epigenetics: A New Frontier
2. Apr 10: Normalization of omic data after 2007

Harvard University

1. Nov 14: Trivial Mathematics but Deep Statistics: Simpson's Paradox and Its Impact on Your Life
2. Nov 15: Who is crazier: Bayes or Fisher?

Department of Biostatistics, University of Washington

1. Dec 6: Clinical Trials and Epidemiology: Reflections of the Statistician for the National Wilms Tumor Study
2. Dec 7: Inference on Hazard Ratios and Survival Probabilities from Two-phase Stratified Samples

Department of Statistics, Stanford University

Oct 5: Statistical Learning with Large Numbers of Predictor Variables

Oct 6: Predictive Learning via Rule Ensembles

Department of Operation Research and Financial Engineering, Princeton University

May 3: Vast-dimensionality and sparsity

May 4: ISIS: A vehicle for the universe of sparsity

Stanford University

Nov 9: Fifty Years Of Empirical Bayes

Nov 10: Correlation And Large-Scale Simultaneous Significance Testing

Department of Statistics, University of Oxford

Sep 14: Graphical Models and their Statistical Interpretations

Sep 15: Graphical Models: Some Technical Developments 

Mathematics and Statistics, Carleton University and McGill University

Apr 23: Probabilistic Phenomena in Mathematics and Science

Apr 24: Probabilistic Phenomena in Mathematics and Science

University of Toronto, Statistics Department

Apr 16: Is the future Bayesian or frequentist?

Apr 18: Is the future Bayesian or frequentist?

Australian National University

1. Sep 28: Data Tuning
2. Oct 26: Estimating Fault Lines and Boundaries