
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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