Department of Statistics Event Calendar

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2023 Bohrer Workshop in Statistics

Event Type
Department of Statistics
Apr 22, 2023   9:00 am - 8:00 pm  



8:30 - 9:00 am

Breakfast – Alma Room 

9:00 - 9:15 am

Opening Remarks – Lincoln Room

9:15 - 9:50 am

Lightning Talks Session 1 

Anwesha Chakravarti: Optimizing Trap Placement to Predict West Nile Virus Cases 

Yifan Chen: Statistical Leverage Score Approximation for Kernel Empirical Risk Minimization 

Robert Garrett: A multivariate space-time dynamic model for characterizing pathways following the Mt. Pinatubo eruption 

Byeongjip Kim: The Node Influence Mixed Membership Stochastic Block Models on Heterogeneous Networks

9:50 - 10:00 am

Break – Alma Room

10:00 - 10:50 am

Lightning Talks Session 2 – Lincoln Room 

Abhishek Ojha: A Conditional Bayesian Approach with Valid Inference for High Dimensional Logistic Regression 

Austin Warner: Online Change Diagnosis Using Physical Models 

Theren Williams: Restricted HMM for Latent Class Attribute Transitions 

Rentian Yao: On the convergence of Coordinate Wasserstein Proximal Gradient Flow 

Yubo Zhuang: Wasserstein K-means for clustering probability distributions

10:50 - 11:00 am

Break – Alma Room 

11:00 - 12:00 pm

Wijsman Lecture by Jelena Bradic: Exploring new venues in double robustness for treatment effects in dynamic settings

12:00 - 1:00 pm

Lunch – Alma Room

1:00 - 1:50 pm

Paper Session I – Lincoln Room

Alton Barbehenn: Biomarker Imputation with Empirical Bayes Tobit Matrix Estimation 

Kaustav Chakraborty: Efficient Model Fitting and Two-Sample Testing for Large Networks via Subsampling 

Hanjia Gao: Dimension-agnostic Change Point Detection

1:50 - 2:00 pm

Break – Alma Room 

2:00 - 2:50 pm

Paper Session II – Lincoln Room

Yuhan Li: Quasi-optimal Reinforcement Learning with Continuous Actions 

Diptarka Saha: Probabilistic Guarantees on Sensitivities of Bayesian Neural Network 

Adam Tonks: Spatiotemporal assessment of regional flooding risk across the contiguous United States using 2-D spline models

2:50 - 3:00 pm

Break – Alma Room

3:00 - 3:50 pm

Norton Session – Lincoln Room

Anamitra Chaudhuri (Honorable Mention): Joint Sequential Detection and Isolation of a Dependence Structure 

Rong Tang (Norton Winner): Bayesian Inference for Risk Minimization via Exponentially Tilted Empirical Likelihood

3:50 - 4:00 pm

Break – Alma Room 

4:00 - 5:00 pm

Bohrer Lecture by Andrew Barron: Information Theory in Statistical Learning: Foundations and a Modern Perspective

5:00 - 6:00 pm

Award Presentations and Poster Session – Alma Room 

6:00 - 8:00 pm

Dinner – Alma Room 

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