A projection-based approach for spatial generalized linear mixed models
Sponsor(s):
Statistical Science
Friday, October 20, 2017
3:30 pm - 4:30 pm
Murali Haran, Penn State
Bayesian Approaches for Dynamic Model Selection: two contributions
Sponsor(s):
Statistical Science
Friday, October 27, 2017
3:30 pm - 4:30 pm
Michele Guindani, University of California, Irvine
An MCMC Approach to Empirical Bayes Inference and Bayesian Sensitivity Analysis via Empirical Processes
Sponsor(s):
Statistical Science
Friday, November 03, 2017
3:30 pm - 4:30 pm
Hani Doss, University of Florida
Meta-Analysis With Multiple Imputation: Constructing Data Banks for Hard-To-Study Populations
Sponsor(s):
Statistical Science
Friday, November 10, 2017
3:30 pm - 4:30 pm
Elly Kaizar, Ohio State
Statistical Concepts for Single-Cell Genomics
Sponsor(s):
Statistical Science
Friday, November 17, 2017
3:30 pm - 4:30 pm
Lior Pachter, Cal Tech
Teaching to Learn: Statistics in Data Science
Sponsor(s):
Statistical Science
Monday, November 27, 2017
2:00 pm - 3:00 pm
David Dalpiaz, University of Illinois
Anchored Bayesian Mixture Models
Sponsor(s):
Statistical Science
Wednesday, November 29, 2017
3:30 pm - 4:30 pm
Deborah Kunkel, The Ohio State University
Approximate MCMC in Theory and Practice
Sponsor(s):
Statistical Science
Friday, December 01, 2017
3:30 pm - 4:30 pm
James Johndrow, Stanford University
A Bayesian Approach to Interpreting Latent Fingerprint Evidence
Sponsor(s):
Statistical Science
Wednesday, December 06, 2017
3:30 pm - 4:30 pm
Maria Tackett, University of Virginia
Estimation of open populations from multiple structurally different data sets
Sponsor(s):
Statistical Science
Friday, December 08, 2017
3:30 pm - 4:30 pm
Lutz Gruber, University of Nebraska-Lincoln
High Dimensional Inference: Semiparametrics, Counterfactuals, and Heterogeneity
Sponsor(s):
Statistical Science
Friday, January 12, 2018
3:30 pm - 4:30 pm
Ying Zhu, Michigan State University
Eigenvalues in multivariate random effects models
Sponsor(s):
Statistical Science
Wednesday, January 17, 2018
3:30 pm - 4:30 pm
Zhou Fan, Stanford
Enabling likelihood-based inference for complex and dependent
Sponsor(s):
Statistical Science
Friday, January 19, 2018
3:30 pm - 4:30 pm
Jason Xu, UCLA
Least squares estimation: beyond Gaussian regression models
Sponsor(s):
Statistical Science
Wednesday, January 24, 2018
3:30 pm - 4:30 pm
Roy Han, Univ. of Washington
Beyond matrices: theory, methods, and applications of higher-order tensors
Sponsor(s):
Statistical Science
Friday, January 26, 2018
3:30 pm - 4:30 pm
Miaoyan Wang, UC Berkeley
Interactive algorithms for multiple hypothesis testing
Sponsor(s):
Statistical Science
Friday, February 02, 2018
3:30 pm - 4:30 pm
Aaditya Ramdas, UC Berkeley
Estimation and testing for two-stage experiments in the presence of interference
Sponsor(s):
Statistical Science
Wednesday, February 07, 2018
3:30 pm - 4:30 pm
Guillaume Basse, Harvard
Constrained low-rank matrix (and tensor) estimation
Sponsor(s):
Statistical Science
Friday, February 23, 2018
3:30 pm - 4:30 pm
Lenka Zdeborova, CNRS and CEA Saclay, France, Currently at Duke for Spring Semester 2018
Information theory and high-dimensional statistical inference
Sponsor(s):
Statistical Science
Friday, March 23, 2018
3:30 pm - 4:30 pm
Galen Reeves, Duke University
Space-Time Modeling of Small Area Data in a Developing World Setting
Sponsor(s):
Statistical Science
Friday, March 30, 2018
3:30 pm - 4:30 pm
Jon Wakefield, University of Washington
Incorporating Uncertainty within Human-in-the-Loop Analytics for Data Exploration
Sponsor(s):
Statistical Science
Friday, April 06, 2018
3:30 pm - 4:30 pm
Leanna House, Virginia Tech
Manifold Data Analysis with Applications to High-Resolution 3D Imaging
Sponsor(s):
Statistical Science
Friday, April 13, 2018
3:30 pm - 4:30 pm
Matthew Reimherr, Penn State University
Space and circular time log Gaussian Cox processes with application to crime event data
Sponsor(s):
Statistical Science
Friday, April 20, 2018
3:30 pm - 4:30 pm
Alan Gelfand, Duke University
Introducing the overlap weights for causal inference
Sponsor(s):
Statistical Science
Friday, August 31, 2018
3:30 pm - 4:30 pm
Fan Li, Duke University Statistical Science
On the Pitman-Yor process with spike and slab base measure
Sponsor(s):
Statistical Science
Friday, September 07, 2018
3:30 pm - 4:30 pm
Antonio Canale, University of Padova, Department of Statistical Sciences
Bayesian Multiple Breakpoint Detection: Mixing Documented and Undocumented Changepoints
Sponsor(s):
Statistical Science
Friday, September 14, 2018
3:30 pm - 4:30 pm
Robert Lund, Clemson University, Mathematical Sciences
Permutation tests in the presence of confounders
Sponsor(s):
Statistical Science
Friday, September 21, 2018
3:30 pm - 4:30 pm
Rina Foygel Barber, University of Chicago
Inference of biological networks with biophysically motivated methods
Sponsor(s):
Statistical Science
Friday, September 28, 2018
3:30 pm - 4:30 pm
Rich Bonneau, New York University
Transfer Learning and Data Alignment in Single Cell Transcriptomics
Sponsor(s):
Statistical Science
Friday, October 12, 2018
3:30 pm - 4:30 pm
Nancy Zhang, Wharton School, University of Pennsylvania
Stochastic process models for animal trajectories
Sponsor(s):
Statistical Science
Friday, October 19, 2018
3:30 pm - 4:30 pm
Mevin Hooten, Colorado State University
The Blessings of Multiple Causes
Sponsor(s):
Statistical Science
Friday, October 26, 2018
3:30 pm - 4:30 pm
Dave Blei, Columbia University
The Little CpG Site That Could (and eight others less so): Developing Effect Size Measures for Mediation Analysis
Sponsor(s):
Statistical Science
Friday, November 02, 2018
3:30 pm - 4:30 pm
Yue Jiang, UNC Department of Biostatistics
Handling Missing Data in Surveys
Sponsor(s):
Statistical Science
Monday, November 05, 2018
3:30 pm - 4:30 pm
Olanrewaju Michael Akande, Department of Statistical Science, Duke University
Monte Carlo Methods and Contingency Tables
Sponsor(s):
Statistical Science
Friday, November 09, 2018
3:30 pm - 4:30 pm
Robert Eisinger, Instructor of Mathematics, Statistics, and Computer Science, St. Olaf College
Using Item Response Theory to Better Understand Forensic Fingerprint Examination
Sponsor(s):
Statistical Science
Monday, November 12, 2018
3:30 pm - 4:30 pm
Amanda Luby, PhD candidate, Carnegie Mellon University.
Web Scraping in the Statistics Curricula: Challenges and Opportunities
Sponsor(s):
Statistical Science
Wednesday, November 14, 2018
3:30 pm - 4:30 pm
Mine Dogucu, Visiting Professor, Denson University
Design and analysis of pragmatic clinical trials to optimize clinical outcomes
Sponsor(s):
Statistical Science
Friday, November 16, 2018
3:30 pm - 4:30 pm
Hayley Belli, Post-Doctoral Fellow, Division of Biostatistics New York University Langone School of Medicine
Covariance change point detection and identification (See abstract for full title)
Sponsor(s):
Statistical Science
Monday, November 19, 2018
3:30 pm - 4:30 pm
Shawn Santo, Ph.D. Candidate at Michigan State University
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
More Events
(60 of 152)