Statistics and Data Science Seminar: Geodesic Mixed Effects Models for Repeatedly Observed/Longitudinal Random Objects
Speaker: Satarupa Bhattacharjee, Penn State University
Choose Year:
Statistics and Data Science Seminar: Doubly High-Dimensional Contextual Bandits: An Interpretable Model for Joint Assortment and Pricing
Speaker: Ran Chen, Massachusetts Institute of Technology
Statistics and Data Science Seminar: Inference for machine learning under dependence
Speaker: Arkajyoti Saha, University of Washington
Statistics and Data Science Seminar: Temporal-spatial Model via Trend Filtering
Speaker: Carlos Madrid Padilla, University of Notre Dame
Statistics and Data Science Seminar: A `robust' framework for statistical inference
Speaker: Arun Kumar Kuchibhotla, Carnegie Mellon University
Statistics and Data Science Seminar: Theory for Cross Validation in Nonparametric Regression
Speaker: Sabyasachi Chatterjee, University of Illinois Urbana-Champaign
Statistics and Data Science Seminar: Change Point Detection via Self-normalization: A Personal Journey
Speaker: Xiaofeng Shao, University of Illinois Urbana-Champaign
TRIADS Speaker Series with Elizabeth F.S. Roberts & Martha María Téllez Rojo
Statistics and Data Science Seminar: Nonparametric sharp bounds and optimal design in police oversight
Speaker: Dean Knox, University of Pennsylvania
Statistics and Data Science Seminar: Sparse Causal Learning: Challenges and Opportunities
Speaker: Linbo Wang, University of Toronto
Statistics and Data Science Seminar: Statistical Inference in Reinforcement Learning
Speaker: Chengchun Shi, London School of Economics and Political Science
Statistics and Data Science Seminar: Unsupervised Statistical Tools for Anomaly Detection: The Case of Healthcare Frauds
Speaker: Fabrizio Ruggeri, Italian National Research Council
Statistics and Data Science Seminar: High-dimensional Information Processing: Optimality and Universality
Speaker: Hong Hu, University of Pennsylvania
TRIADS Speaker Series with Julia Stoyanovich
Statistics and Data Science Seminar: Inverses of Matern Covariances on Grids
Speaker: Joe Guinness, Cornell University
Statistics and Data Science Seminar: Pattern Graphs: a Graphical Approach to Nonmonotone Missing Data
Speaker: Yen-Chi Chen, University of Washington
Statistics and Data Science Seminar: Filtering (Data Assimilation) in High Dimensions: Sequential MCMC with Applications to Lagrangian Data Assimilation with Unknown Data Location
Speaker: Hamza Ruzayqat, King Abdullah University of Science and Technology
Statistics and Data Science Seminar: Bootstrapping linear and non-linear spectral statistics in high dimensions
Speaker: Miles Lopes, University of California - Davis
TRIADS Speaker Series with Dolores Albarracín
Statistics and Data Science Seminar: Getting Inference Right with LLM Annotations in the Social Sciences: A General Framework of Using Predicted Variables in Downstream Analysis
Speaker: Brandon Stewart, Princeton University
Thesis Oral Defense: Inference for Time Series in Change Points and Statistical Learning
Speaker: Jiaqi Li, Washington University in St. Louis
Workshop on Translational Research on Data Heterogeneity
Hosted by Department of Statistics and Data Science, Washington University in St. Louis, with support from National Science Foundation Grants DMS-1951980 and DMS-2406154
Thesis Oral Defense: Assessing reproducibility of Brain-behavior associations using bootstrap aggregation methods
Speaker: Zhetao Chen, Washington University in St. Louis
Statistics and Data Science Seminar: Towards a more flexible BART
Speaker: Alexander Volfovsky, Duke University
Statistics and Data Science Seminar: Boosting e-BH via conditional calibration
Speaker: Zhimei Ren, University of Pennsylvania
TRIADS Speaker Series with Catherine Knight Steele
Statistics and Data Science Seminar: An Interdisciplinary Approach for Identifying Partisan Gerrymandering
Speaker: Wendy Cho, Vanderbilt University
Award Ceremony, 2024
Installation of Xuming He as the Kotzubei Beckmann Distinguished Professor
Reading Days and Exams, Spring 2024
Candidacy oral presentation: Statistical Inference for Integrated Volatility
Speaker: Tianwei Zhou, Washington University in St. Louis
Commencement 2024
First Summer Class Session Begins, Summer 2024
Memorial Day Holiday 2024 - no classes
Independence Day Holiday 2024 - no classes
Oral Defense: Estimation of Integrated Volatility Functional & Behavior of the Bandwidth Selector with Kernel Spot volatility Estimators
Speaker: Jincheng Pang, Washington University in St. Louis
WashU JSM 2024 Alumni and Friends Reception
Last Summer Class Session Ends, Summer 2024
First Day of Classes, Fall 2024
Labor Day 2024 - no classes
Statistics and Data Science Seminar: Casual Inference in the Presence of Interference: Estimation and Testing Problems
Speaker: Shuangning Li, University of Chicago
Statistics and Data Science Seminar: A Martingale Theory of Evidence
Speaker: Aaditya Ramdas, Carnegie Mellon University
Skills and Professional Advancement Series
Hosted by Dr. Nan Lin and Dr. Hong Hu
Dissecting Double Dipping in Statistical Tests After Clustering
Speaker: Jingyi Li, UCLA
On the Pointwise Behavior of Recursive Partitioning and Its Implications for Heterogeneous Causal Effect Estimation
Speaker: Matias Cattaneo, Princeton University
Generalization error of min-norm interpolators in transfer learning
Pragya Sur, Harvard University
Statistical Inference on Latent Space Models for Network Data
Ji Zhu, University of Michigan
SDS, Skills and Professional Advancement Series
*SDS Grad Student Event Only*
Fall Break 2024 - no classes
On Statistical Inference in Observational Studies
Rajarshi Mukherjee, Havard University
Coevolving Latent Space Network with Attractors Models for Polarization
Speaker: Eric Kolacyzk, McGill University
Offline Reinforcement Learning: A Data-Driven Approach for Sequential Decision Making
Speaker: Chongjie Zhang
Bo Li appointed as Co-Director of TRIADS
Statistics and Data Science Seminar on October 30
Speaker: Jonathan Niles-Weed, New York University
Graph Learning for Functional Neuronal Connectivity
Speaker: Genevera Allen, Columbia University
Revisiting Optimism and Model Complexity in the Wake of Overparameterized Machine Learning
Speaker: Ryan Tibshirani, University of California, Berkeley
Data Science, Statistics, and Health, with a Focus on Statistical Learning and Sparsity and Applications to Biomedicine
Speaker: Rob Tibshirani ( Stanford University )
How Statistics Can Advance Large Language Models: Fairness Alignment and Watermarking
Speaker: Weijie Su, University of Pennsylvania
Accurate and efficient data point removal for high-dimensional settings
Speaker: Arian Maleki, associate professor in the Department of Statistics at Columbia University.
Thanksgiving Break 2024 - no classes
Last Day of Classes, Fall 2024
Reading Days and Exams, Fall 2024
Robust Causal Inference on Public Health Interventions Using Epidemic Models
Heejong Bong,
Postdoctoral Fellow, Dept of Statistics University of Michigan
Semiparametric Causal Mediation Analysis in Cluster-randomized Experiments
Chao Cheng,
PhD Candidate in Biostatistics, Yale School of Public Health