## Statistical inference for infectious disease modeling

Sponsor(s):
Statistical Science

Wednesday, January 16, 2019

3:30 pm - 4:30 pm

Po-Ling Loh, University of Wisconsin - Madison

## Support points - a new way to reduce big and high-dimensional data

Sponsor(s):
Statistical Science

Friday, January 18, 2019

3:30 pm - 4:30 pm

Simon Tsz Fung Mak, Georgia Tech

## Towards a mathematical theory of development

Sponsor(s):
Statistical Science

Wednesday, January 23, 2019

3:30 pm - 4:30 pm

Geoffrey Schiebinger, Postdoctoral fellow in the MIT Center for Statistics and the Klarman Cell Observatory at the Broad Institute of MIT and Harvard

## Data Denoising for Single-cell RNA sequencing

Sponsor(s):
Statistical Science

Friday, January 25, 2019

3:30 pm - 4:30 pm

Jingshu Wang, UPENN

## Scalable Importance Tempering and Bayesian Variable Selection

Sponsor(s):
Statistical Science

Wednesday, January 30, 2019

3:30 pm - 4:30 pm

Giacomo Zanella, Bocconi University

## Stability-driven deep model interpretation and provably fast MCMC sampling

Sponsor(s):
Statistical Science

Friday, February 01, 2019

3:30 pm - 4:30 pm

Yuansi Chen, University of California, Berkeley

## Algebraic Structure in Hidden Variable Models

Wednesday, February 13, 2019

3:30 pm - 4:30 pm

Elina Robeva, MIT - Massachusetts Institute of Technology

## Calibration Concordance for Astronomical Instruments via Multiplicative Shrinkage

Friday, February 22, 2019

3:30 pm - 4:30 pm

Yang Chen, Assistant Professor of Statistics, Research Assistant Professor for MIDAS, University of Michigan

## Getting your arrays in order with convex optimization

Friday, March 08, 2019

3:30 pm - 4:30 pm

Eric Chi, Assistant Professor, NC State

## Big (Network) Data: Challenges and Opportunities for Data Science

Friday, March 22, 2019

3:30 pm - 4:30 pm

Patrick J. Wolfe, Frederick L. Hovde Dean of Science and Miller Family Professor of Statistics and Computer Science, Purdue University; IEEE Signal Processing Society Data Science Distinguished Lecturer

## Learning Coexpression Networks from Single Cell Gene Expression

Friday, April 12, 2019

3:30 pm - 4:30 pm

Andrew McDavid, Assistant Professor, Dept. of Biostatistics and Computational Biology, University of Rochester

## Large-scale evidence generation across a network of databases (LEGEND) for hypertension: real-world, reliable and reproducible

Wednesday, April 17, 2019

3:30 pm - 4:30 pm

Marc Suchard, Professor in the Departments of Biostatistics, of Biomathematics and of Human Genetics in the UCLA Fielding School of Public Health and David Geffen School of Medicine at UCLA

## Statistical Science Faculty Research Presentations

Friday, September 06, 2019

3:30 pm - 4:30 pm

Mike West, Fan Li, Amy Herring and Hau-Tieng Wu, Duke Statistical Science Faculty

## Scaling and Generalizing Approximate Bayesian Inference

Friday, September 13, 2019

3:30 pm - 4:30 pm

David Blei, Columbia University

## Causal inference under spillover and contagion: structural versus agnostic methods

Friday, September 20, 2019

3:30 pm - 4:30 pm

Forrest Crawford, Yale School of Public Health

## PageRank on Directed Complex Networks

Friday, September 27, 2019

3:30 pm - 4:30 pm

Mariana Olvero-Cravioto, UNC

## Markov-Modulated Hawkes Processes for Sporadic and Bursty Event Occurrences

Friday, October 04, 2019

3:30 pm - 4:30 pm

Dr. Tian Zheng, Columbia University

## Spiked Laplacian Graphs - harnessing the spectral graph theory in the Bayesian framework

Friday, October 11, 2019

3:30 pm - 4:30 pm

Leo Duan, University of Florida

## Bayesian Categorical Matrix Factorization via Double Feature Allocation

Friday, October 18, 2019

3:30 pm - 4:30 pm

Peter Mueller, University of Texas - Austin

## Sparsity selection in high-dimensional Bayesian vector autoregressive models based on a pseudo-likelihood approach

Friday, October 25, 2019

3:30 pm - 4:30 pm

Kshitij Khare, University of Florida

## +DS IPLE: Biomedical Data Science and Machine Learning Applications in Healthcare

Sponsor(s):
+DataScience (+DS), Biomedical Engineering (BME), Biostatistics and Bioinformatics, Information Initiative at Duke (iiD), Machine Learning, and Pratt School of Engineering

Wednesday, October 30, 2019

4:30 pm - 6:30 pm

Jessilyn Dunn

## Kernel tests of goodness-of-fit using Stein's method

Friday, November 01, 2019

3:30 pm - 4:30 pm

Arthur Gretton - Gatsby Computational Neuroscience Unit - UCL

## An Exact Auxiliary Variable Gibbs Sampler for a Class of Diffusions

Friday, November 08, 2019

3:30 pm - 4:30 pm

Vinayak Rao, Purdue

## A Bayesian Approach to Mapping Directional Brain Networks

Friday, November 15, 2019

3:30 pm - 4:30 pm

Tingting Zhang, University of Virginia

## Shuffled monotone regression

Friday, November 22, 2019

3:30 pm - 4:30 pm

Charles Doss, University of Minnesota

## Edge-Selection Priors for Graphical Models and Applications to Complex Biological Data

Friday, December 06, 2019

3:30 pm - 4:30 pm

Marina Vannucci, Rice University

## Stochastic nets and Bayesian regularization

Monday, January 06, 2020

3:30 pm - 4:30 pm

Joshua Bon, Queensland University of Technology & ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS)

## 'Statistics 101' for Network Data Objects

Friday, January 17, 2020

3:30 pm - 4:30 pm

Eric Kolaczyk, Boston University

## Latent variable models: from spectral methods to non-convex optimization

Wednesday, January 22, 2020

3:30 pm - 4:30 pm

Kaizheng Wang, Princeton

## Cancelled-Handling Sampling and Selection Bias in Association Studies Embedded in Electronic Health Records

Friday, January 24, 2020

3:30 pm - 4:30 pm

Bhramar Mukherjee, University of Michigan

## Testing high-dimensional linear hypotheses through spectral shrinkage

Friday, January 31, 2020

3:30 pm - 4:30 pm

Debashis Paul, University of California, Davis

## Statistical and computational perspectives on latent variable models

Wednesday, February 05, 2020

3:30 pm - 4:30 pm

Nhat Ho, Berkeley

## Geospatial Technologies for Ride-Hailing and Emergency Vehicle Fleets

Friday, February 07, 2020

3:30 pm - 4:30 pm

Dawn Woodard, Director of Data Science (Maps, Forecasting, and Experimentation),Uber

## Towards seamless carbon cycle prediction: from data assimilation to emergent constraints

Friday, February 14, 2020

3:30 pm - 4:30 pm

Kevin Bowman, JPL Science, NASA

## Probably Approximately Correct Causal Discovery

Friday, February 21, 2020

3:30 pm - 4:30 pm

David Page, Department of Biostatistics and Bioinformatics, Duke University School of Medicine

## Bayes from Moments

Friday, February 28, 2020

3:30 pm - 4:30 pm

Siddhartha Chib, Washington University, St. Louis

## Sample size considerations for precision medicine

Sponsor(s):
Statistical Science, Biostatistics and Bioinformatics, and Information Initiative at Duke (iiD)

Wednesday, March 04, 2020

3:30 pm - 4:30 pm

Eric Laber, NC State University

## Overcoming weakly identifiable mixture models with more exchangeable data

Friday, March 06, 2020

3:30 pm - 4:30 pm

Long Nguyen, University of Michigan

## CANCELLED-Statistical Science Faculty Research Presentations

**CANCELED**

Friday, March 20, 2020

3:30 pm - 4:30 pm

## CANCELLED-Analyzing Data Full of Holes: Topological Data Analysis

**CANCELED**

Friday, April 03, 2020

3:30 pm - 4:30 pm

Jessica Cisewski, Yale

## CANCELLED-Bayesian Uncertainty

**CANCELED**

Friday, April 10, 2020

3:30 pm - 4:30 pm

Stephen Walker, University of Texas-Austin

## CANCELLED-Yi Yang, McGill University

**CANCELED**

Friday, April 17, 2020

3:30 pm - 4:30 pm

Yi Yang, McGill University

## CANCELLED-Rebecca Hubbard, Perelman School of Medicine, University of Pennsylvania

**CANCELED**

Friday, April 24, 2020

3:30 pm - 4:30 pm

Rebecca Hubbard, Perelman School of Medicine, University of Pennsylvania

## Likelihood-based Inference for Stochastic Epidemic Models via Data Augmentation

Sponsor(s):
Statistical Science

Friday, September 24, 2021

3:30 pm - 4:30 pm

Jason Xu, Duke University

## Reed-Muller codes achieve capacity on BMS channels

Sponsor(s):
Statistical Science

Friday, January 21, 2022

3:30 pm - 4:30 pm

Galen Reeves, Associate Professor, Duke University Statistical Science

## Experimental design for studying political polarization

Sponsor(s):
Statistical Science

Friday, January 28, 2022

3:30 pm - 4:30 pm

Alexander Volfovsky, Assistant Professor, Statistical Science, Duke University

## Machine Learning Approach to Kaggle COVID 19 Global Forecasting Challenge

Sponsor(s):
Statistical Science

Wednesday, March 23, 2022

3:30 pm - 4:45 pm

Funda Güneş, Master's Director, Duke University

## Characterizing the Type 1-Type 2 Error Trade-off for SLOPE

Sponsor(s):
Statistical Science

Friday, March 25, 2022

3:30 pm - 4:30 pm

Cynthia Rush, Assistant Professor, Columbia University, Statistics

## Controlled Discovery and Localization of Signals via Bayesian Linear Programming

Sponsor(s):
Statistical Science

Friday, April 01, 2022

3:30 pm - 4:30 pm

Lucas Janson, Assistant Professor, Statistics and Affiliate, Computer Science, Harvard University

## Functional Models for Time Varying Random Objects

Sponsor(s):
Statistical Science

Friday, April 08, 2022

3:30 pm - 4:30 pm

Paromita Dubey, Assistant Professor, Data Sciences and Operations, USC Marshall School of Business

## Arabic Night 2022

Sponsor(s):
Asian & Middle Eastern Studies (AMES)

Wednesday, April 13, 2022

6:00 pm

## Variable Selection and Prioritization in Bayesian Machine Learning Methods

Sponsor(s):
Statistical Science

Friday, April 15, 2022

3:30 pm - 4:30 pm

Lorin Crawford, RGSS Assistant Professor, Biostatistics, Brown University

## Revisiting Gelman-Rubin with Global Centering

Sponsor(s):
Statistical Science

Monday, May 09, 2022

12:00 pm - 1:00 pm

Dootika Vats is an Assistant Professor in the Department of Mathematics and Statistics at the Indian Institute of Technology Kanpur, India.

## Bayesian Functional Principal Component Analysis using Relaxed Mutually Orthogonal Processes

Sponsor(s):
Statistical Science

Friday, September 09, 2022

3:30 pm - 4:30 pm

James Matuk, Postdoctoral Associate, Duke University

## Semiparametric discrete data regression with Monte Carlo inference and prediction

Sponsor(s):
Statistical Science

Friday, September 16, 2022

3:30 pm - 4:30 pm

Daniel Kowal, Dobelman Family Assistant Professor Department of Statistics, Rice University

## Unsupervised tree boosting for learning probability distributions

Sponsor(s):
Statistical Science

Friday, September 23, 2022

3:30 pm - 4:30 pm

Li Ma, Associate Professor of Statistical Science, Duke University

## Algorithmic Stochastic Localization for the Sherrington-Kirkpatrick Model

Sponsor(s):
Statistical Science

Friday, October 07, 2022

3:30 pm - 4:30 pm

Mark Sellke, Assistant Professor, Dept. of Statistics, Harvard

## The Shadow Carceral State and Racial Inequality

Sponsor(s):
Statistical Science

Friday, October 14, 2022

3:30 pm - 4:30 pm

Ted Enamorado, Washington University at St Louis

## Comparison of Markov chains via weak Poincaré inequalities with application to pseudo-marginal MCMC

Sponsor(s):
Statistical Science

Friday, October 21, 2022

3:30 pm - 4:30 pm

Andi Wang, Senior Research Associate, School of Mathematics Research, University of Bristol-Warwick

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