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
Scalable community detection in massive networks via predictive inference
Sponsor(s):
Statistical Science
Friday, October 28, 2022
3:30 pm - 4:30 pm
Srijan Sengupta, Assistant Professor, NC State University
Disentangling confounding and nonsense associations due to dependence
Sponsor(s):
Statistical Science
Friday, November 04, 2022
3:30 pm - 4:30 pm
Elizabeth Ogburn, Associate Professor, Johns Hopkins University
Representation Learning: A Causal Perspective
Sponsor(s):
Statistical Science
Friday, November 11, 2022
3:30 pm - 4:30 pm
Yixin Wang, Assistant Professor, Statistics, University of Michigan
Interpretable sensitivity analysis for the Baron–Kenny approach to mediation with unmeasured confounding
Friday, November 18, 2022
3:30 pm - 4:30 pm
Peng Ding, University of California, Berkeley
High Dimensional Random Forests Estimation and Inference
**CANCELED**
Friday, December 02, 2022
3:30 pm - 4:30 pm
Yingying Fan, Professor, USC Marshall
Structured prior distributions for the covariance matrix in latent factor models
Sponsor(s):
Statistical Science
Friday, December 09, 2022
3:30 pm - 4:30 pm
Sarah Heaps, Associate Professor, Statistics, Durham University
Make your own kind of sparse DAG; Fit your own special scalable Gaussian process. Bayesian geostatistics for massive data
Sponsor(s):
Statistical Science
Friday, January 13, 2023
3:30 pm - 4:30 pm
Dr. Michele Peruzzi, Postdoctoral Associate, Duke Statistical Science
3D Bivariate Spatial Modelling of Argo Ocean Temperature and Salinity Profiles
Sponsor(s):
Statistical Science
Wednesday, January 18, 2023
3:30 pm - 4:30 pm
Dr. Mary Salvaña, Statistician / Postdoctoral Research Fellow, University of Houston
Hierarchical Structures in Bayesian Statistics
Sponsor(s):
Statistical Science
Friday, January 20, 2023
3:30 pm - 4:30 pm
Filippo Ascolani, PhD student, Statistics, Bocconi University,
Identifiable Deep Generative Models via Sparse Decoding
Sponsor(s):
Statistical Science
Wednesday, January 25, 2023
3:30 pm - 4:30 pm
Dr. Gemma Moran, Postdoctoral Associate, Columbia Data Science Institute
To Adjust or not to Adjust? Estimating the Average Treatment Effect in Randomized Experiments with Missing Covariates
Sponsor(s):
Statistical Science
Friday, January 27, 2023
3:30 pm - 4:30 pm
Dr. Anqi Zhao, Assistant Professor, National University of Singapore
Undergrads Take Over StatSci Seminar!
Sponsor(s):
Statistical Science
Friday, February 10, 2023
3:30 pm - 4:30 pm
Statistical Science Undergraduate Students
Harvard Business School - Information Session (MBA and 2+2 Program)
Sponsor(s):
Trinity College
Wednesday, March 01, 2023
7:00 pm - 8:30 pm
Mission Imputable: Correcting for Berkson Error When Imputing a Censored Covariate
Sponsor(s):
Statistical Science
Friday, March 10, 2023
3:30 pm - 4:30 pm
Tanya P. Garcia, Associate Professor of Biostatistics, UNC-Chapel Hill, Gillings School of Public Health
Design-Based Anytime-Valid Causal Inference
Sponsor(s):
Statistical Science
Friday, March 31, 2023
3:30 pm - 4:30 pm
Iavor Bojinov, Assistant Professor, Business Administration, Harvard Business School
On the Convergence of Coordinate Ascent Variational Inference
Sponsor(s):
Statistical Science
Friday, April 07, 2023
3:30 pm - 4:30 pm
Anirban Bhattacharya, Professor, Department of Statistics, Texas A&M University
The role of skewed distributions in Bayesian inference: conjugacy, scalable approximations and asymptotics
Sponsor(s):
Statistical Science
Friday, April 14, 2023
3:30 pm - 4:30 pm
Daniele Durante, Assistant Professor, Bocconi University
Finite-dimensional discrete random structures and Bayesian clustering
Sponsor(s):
Statistical Science
Friday, April 21, 2023
3:30 pm - 4:30 pm
Tomasso Rigon, Assistant Professor, University of Milano Bicocca
A Bayesian Nonparametric Approach to Geographic and Two-Dimensional Regression Discontinuity Designs
Sponsor(s):
Statistical Science
Friday, April 28, 2023
3:30 pm - 4:30 pm
Luke Miratrix, Associate Professor, Harvard University
Ecological Modeling via Bayesian Nonparametric Species Sampling Priors
Sponsor(s):
Statistical Science
Tuesday, June 20, 2023
8:30 am - 10:30 am
Alessandro Zito
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