Statistics and Data Science Seminar Series : Department of Mathematics and Statistics : UMass Amherst

Upcoming Statistics and Data Science Seminars

Sep

1:30 pm - 2:30 pm ET

Xiaoyu Chen: Distribution-in-distribution-out Regression

Spring 2024

Date	Speaker	Title
Wed. 2/7	Ted Westling University of Massachusetts Amherst	Debiased inference for a covariate-adjusted regression function
Wed. 2/14	Katherine Moore Amherst College	Cohesion: A Social Perspective on Clustering
Wed. 2/21	Xi Ning Colby College	A semiparametric Cox-Aalen transformation model with censored data
Wed. 2/28	James Matuk University of Pittsburgh	Bayesian modeling of nearly mutually orthogonal processes
Wed. 3/6	Carlos Soto University of Massachusetts Amherst	Applications of Elastic Shape Analysis
Wed. 3/13	Maryclare Griffin UMass Amherst	Log-Gaussian Cox process modeling of large spatial lightning data using spectral and Laplace approximations
Wed. 3/27	Tim Rudner	Data-Driven Priors for Trustworthy Machine Learning
Wed. 4/10	Claire Bowen Urban Institute	Navigating Data Privacy in Public Policy to Responsibly Represent People in Data
Wed. 4/17	Chih-Li Sung Michigan State University	Stacking Designs: Designing Multifidelity Computer Experiments with Target Predictive Accuracy
Wed. 4/24	Peng Ding UC Berkeley	Causal inference in network experiments: regression-based analysis and design-based properties

Fall 2023

Date	Speaker	Title
Wed. 9/13	Rebecca Kurtz-Garcia Smith College	Bandwidth Selection for Zero Lugsail Estimators
Wed. 9/20	Tirthankar Dasgupta Rutgers University	Design-based inference: thoughts, methods, algorithms
Wed. 9/27	Burcu Eke Rubini University of New Hampshire	Mixed Models and Q-Connectivity Graphs for Children’s Play Networks
Wed. 10/4	Qiong Zhang Clemson University	Statistical Designs for Network A/B Testing
Wed. 10/11	Yuxin Tao Tsinghua University	Statistical Inference for stable asymmetric GARCH models
Wed. 10/18	Yiqi (Annie) Tang Colby College	Empirical priors inference in sparse high-dimensional generalized linear models
Wed. 10/25	David Jensen University of Massachusetts Amherst	Do observational causal inference methods really work?
Wed. 11/1	Kengo Kato Cornell University	Entropic optimal transport: stability, limit theorems, and algorithms
Wed. 11/8	Dipak Dey University of Connecticut	Generalized Variable Selection Algorithms for Gaussian Process Models
Wed. 11/15	Arman Oganisian Brown University	Bayesian Semiparametric Models for Informatively Timed Sequential Treatments
Fri. 12/8	Maoran Xu Duke University	Identifiable and interpretable nonparametric factor analysis
Mon. 12/11	Jing Ouyang University of Michigan	Covariate-Adjusted Generalized Factor Analysis with Application to Testing Fairness
Wed. 12/13	Nathan Wycoff	Exploring and Optimizing Computational Models with Gaussian Processes
Thu. 12/14	Arkajyoti Saha	Inference for machine learning under dependence
Fri. 12/15	Satarupa Bhattacharjee	Single Index Fréchet Regression

Department of Mathematics and Statistics

Award-winning teaching, research opportunities, and interdisciplinary programs in a diverse, inclusive community of excellence.

Lederle Graduate Research Tower, 1654
University of Massachusetts Amherst
710 N. Pleasant Street
Amherst, MA 01003-9305, USA

Department Phone: (413) 545-2762
Department Fax: (413) 545-1801
Department Office: LGRT 1657