Name: 2022 Joint Statistical Meetings
Start: 2022-08-06T07:00:00+00:00
End: 2022-08-11
Location: Walter E. Washington Convention Center

Conference Program Home
My Program

All Times EDT

Legend:
CC = Walter E. Washington Convention Center M = Marriott Marquis Washington, DC
* = applied session ! = JSM meeting theme

Activity Details

3 * !	Sun, 8/7/2022, 2:00 PM - 3:50 PM	CC-152A
New Developments and Challenges for Dynamic Individualized Treatments — Invited Papers
Section on Statistical Learning and Data Science, IMS, Biometrics Section
Organizer(s): Annie Qu, UC Irvine
Chair(s): Annie Qu, UC Irvine
2:05 PM	Optimal Treatment Regime Estimation for a Target Population with Summary Statistics Only Wenbin Lu, North Carolina State University; Shu Yang, North Carolina State University; Jianing Chu, North Carolina State University
2:30 PM	Constructing Stabilized Dynamic Surveillance Rules for Optimal Monitoring Schedule Xinyuan Dong, Amazon Inc; Yingye Zheng, Fred Hutchinson Cancer Research Center; Yingqi Zhao, Fred Hutchinson Cancer Research Center
2:55 PM	A Proximal Temporal Consistency Approach for Infinite Horizon Dynamic Treatment Regime Ruoqing Zhu, University of Illinois at Urbana-Champaign
3:20 PM	Data adaptive estimation of individualized treatment strategies Ashkan Ertefaie, University of Rochester
3:45 PM	Floor Discussion

8 * !	Sun, 8/7/2022, 2:00 PM - 3:50 PM	CC-150B
The Best of AOAS — Invited Papers
IMS, Section on Statistical Consulting, Section on Statistical Learning and Data Science, Text Analysis Interest Group
Organizer(s): Karen Kafadar, University of Virginia
Chair(s): Karen Kafadar, University of Virginia
2:05 PM	Crime Linkage Detection by Spatial-Temporal-Textual Point Processes Yao Xie, Georgia Institute of Technology; Shixiang Zhu, Georgia Institute of Technology
2:35 PM	Integrating Geostatistical Maps and Infectious Disease Ttransmission Models Using Adaptive Multiple Importance Sampling Renata Retkute, University of Cambridge; Panayiota Touloupou, University of Birmingham; Maria-Gloria Basanez, Imperial College London; Simon E.F. Spencer, University of Warwick; Christopher A Gilligan, University of Cambridge
3:05 PM	Monitoring Vaccine Safety by Studying Temporal Variation of Adverse Events Using Vaccine Adverse Event Reporting System Jing Huang, University of Pennsylvania; Yi Cai, AT&T Services, Inc.; Jingcheng Du, Melax Tech; Ruosha Li, The University of Texas Health Science Center at Houston; Susan Ellenberg, University of Pennsylvania; Sean Hennessy, University of Pennsylvania; Cui Tao, University of Texas Health Science Center at Houston; Yong Chen, University of Pennsylvania
3:35 PM	Floor Discussion

11 * !	Sun, 8/7/2022, 2:00 PM - 3:50 PM	CC-150A
Modern Machine Learning Tools for Social Science — Invited Papers
Social Statistics Section, IMS, Section on Statistical Learning and Data Science, Text Analysis Interest Group
Organizer(s): Jiashun Jin, Carnegie Mellon University
Chair(s): Rui Song, North Carolina State University
2:05 PM	Evidence-Based Elections Presentation Philip B Stark, UC Berkeley
2:35 PM	Community Detection in Networks with Covariates Wanjie Wang, National University of Singapore
3:05 PM	The Citation Behavior of Statisticians Jiashun Jin, Carnegie Mellon University; Tracy Ke, Harvard University; Pengsheng Ji, University of Georgia; Wanshan Li, Carnegie Mellon University
3:35 PM	Floor Discussion

31	Sun, 8/7/2022, 2:00 PM - 3:50 PM	CC-153
Statistical Inference of Causality and Structure — Contributed Papers
IMS
Chair(s): Min Xu, Rutgers University
2:05 PM	Bayesian Generalized Linear Model for Difference of Over or Under Dispersed Counts Andrew W Swift, University of Nebraska at Omaha; Kimberly Sellers, Georgetown University
2:20 PM	A Restricted Subset Selection Procedure for Selecting the Largest Normal Mean Under Heteroscedasticity Elena M Buzaianu, University of North Florida; Pinyuen Chen, Syracuse University; Lifang Hsu, Lemoyne College
2:35 PM	The Multiple Tuning Problem in Sparse PCA and an Empirical Bayes Solution Joonsuk Kang, University of Chicago; Matthew Stephens, University of Chicago
2:50 PM	Confidence Interval Estimation of the Common Mean of Several Gamma Populations Li Yan, Roswell Park Comprehensive Cancer Center
3:05 PM	A One-Sided Multinomial Hypothesis Test for Unsupervised Anomaly Detection Danielle Gewurz, Deloitte Consulting; Bill Roberts, Deloitte Consulting; Lun Li, Deloitte Consulting; Morgan DeHart, Deloitte Consulting
3:20 PM	No Star Is Good News: A Unified Look at Rerandomization Based on P-Values from Covariate Balance Tests Anqi Zhao, National University of Singapore; Peng Ding, University of California Berkeley
3:35 PM	The Promises of Parallel Outcomes Ying Zhou, University of Toronnto; Dehan Kong, University of Toronto; Linbo Wang, University of Toronto

45 * !	Sun, 8/7/2022, 4:00 PM - 5:50 PM	CC-150B
Recent Development in Mobile/Wearable Device Data Analysis — Invited Papers
Health Policy Statistics Section, ENAR, IMS
Organizer(s): Jingjing Zou, University of California at San Diego (UCSD)
Chair(s): Loki Natarajan, University of California at San Diego (UCSD)
4:05 PM	A Novel Functional Data Analysis Approach to Modeling Longitudinal Changes in Physical Activity Patterns Jingjing Zou, University of California at San Diego (UCSD); Tuo Lin, University of California San Diego; Chongzhi Di, Fred Hutchinson Cancer Research Center; John Bellettiere, UCSD; Marta Jankowska, Beckman Research Institute, City of Hope; Sheri J. Hartman, University of California, San Diego; Dorothy D. Sears, Arizona State University and University of California, San Diego; Andrea LaCroix, UCSD; Cheryl Rock, University of California, San Diego; Loki Natarajan, University of California at San Diego (UCSD)
4:30 PM	Distributional Data Analysis via Quantile Functions and Its Application to Modeling Digital Biomarkers Vadim Zipunnikov, Johns Hopkins University, Bloomberg School of Public Health; Rahul Ghosal, Johns Hopkins University, Bloomberg School of Public Health
4:55 PM	Improving Efficiency of Causal Excursion Effect Estimation via Machine Learning Tianchen Qian, University of California, Irvine; Zhaoxi Cheng, Harvard University
5:20 PM	Measuring Variability in Rest-Activity Rhythms with Application to Characterizing Symptoms of Depression Robert T Krafty, Emory University; Haoyi Fu, University of Pittsburgh; Jessica Graves, University of Pittsburgh; Scott Bruce, Texas A&M University; Martica Hall, University of Pittsburgh; Stephen Smagula, University of Pittsburgh
5:45 PM	Floor Discussion

47 * !	Sun, 8/7/2022, 4:00 PM - 5:50 PM	CC-152B
Causal Inference in the Presence of Nuisance Parameters: Latest Developments — Invited Papers
IMS, ENAR, Section on Statistical Learning and Data Science
Organizer(s): Judith Jacqueline Lok, Boston University
Chair(s): Qingyan Xiang, Boston University
4:05 PM	Automatic Debiased Machine Learning via Neural Nets for Generalized Linear Regression Presentation Whitney Newey, MIT Economics; Victor Chernozhukov, MIT Economics; Vasilis Syrgkanis, Microsoft Research; Victor Quintas-Martinez, MIT Economics
4:30 PM	Sequentially Debiased Estimation of Identified Total Effects in Causal Graphical Models with Hidden Variables Andrea ROTNITZKY, Universidad Torcuato Di Tella; Ezequiel Smucler, Glovo; James M Robins, Harvard University
4:55 PM	How Estimating Nuisance Parameters Often Reduces the Variance (With Variance Correction) Judith Jacqueline Lok, Boston University
5:20 PM	Discussant: Oliver Dukes, University of Pennsylvania
5:40 PM	Floor Discussion

51 !	Sun, 8/7/2022, 4:00 PM - 5:50 PM	CC-207B
BFF: Innovation in Statistical Foundations — Topic Contributed Papers
Section on Bayesian Statistical Science, IMS, International Statistical Institute
Organizer(s): Jan Hannig, University of Noerth Carolina at Chapel Hill
Chair(s): Hari Iyer, National Institute of Standards & Technology
4:05 PM	Fiducial Made Sexy Thomas Lee, UC Davis
4:25 PM	Conformal Predictors Constructed from Generalized Fiducial Inference Jonathan P Williams, North Carolina State University
4:45 PM	Conformal Prediction with Knowledge Transfer Linjun Zhang, Rutgers University
5:05 PM	Warrant and Severity in Statistical Inference Ruobin Gong, Rutgers University
5:25 PM	Discussant: Jan Hannig, University of Noerth Carolina at Chapel Hill
5:45 PM	Floor Discussion

55 * !	Sun, 8/7/2022, 4:00 PM - 5:50 PM	CC-102A
Complex Functional and Non-Euclidean Data Analysis — Topic Contributed Papers
Section on Nonparametric Statistics, Section on Statistical Computing, IMS
Organizer(s): Kuang-Yao Lee, Temple University
Chair(s): Solea Eftychia, ENSAI École Nationale de Statistique et Analyse de l'Information
4:05 PM	Testing Marginal Homogeneity for Functional Data Jane-Ling Wang, University of California, Davis; Changbo Zhu, University of California, Davis
4:25 PM	Pure Differential Privacy in Functional Data Analysis Matthew Reimherr, Penn State University; Haotian Lin, Penn State University
4:45 PM	Fréchet Single Index Models for Object Response Regression Alexander Petersen, Brigham Young University; Aritra Ghosal , University of California, Santa Barbara ; Wendy Meiring , University of California Santa Barbara
5:05 PM	Functional Sufficient Dimension Reduction Through Average Fréchet Derivatives Kuang-Yao Lee, Temple University; Lexin Li, University of California, Berkeley
5:25 PM	Nonlinear Two-Dimensional PCA Joni Virta, University of Turku; Andreas Artemiou, Cardiff University
5:45 PM	Floor Discussion

93 * !	Mon, 8/8/2022, 8:30 AM - 10:20 AM	CC-144B
Recent Advances in Statistical Inference on Network Data — Invited Papers
IMS, Section on Nonparametric Statistics, International Indian Statistical Association
Organizer(s): Sharmodeep Bhattacharyya, Oregon State University
Chair(s): Sharmodeep Bhattacharyya, Oregon State University
8:35 AM	Manifold Learning for Subsequent Inference Carey E Priebe, Johns Hopkins University
9:00 AM	Edge Differentially Private Estimation in the Network Beta-Model via Jittering and Method of Moments Jinyuan Chang, Southwestern University of Finance & Economics; Qiao Hu, Southwestern University of Finance & Economics; Eric Kolaczyk, Boston University; QIWEI YAO, London School of Economics; Fengting Yi, Southwestern University of Finance & Economics
9:25 AM	Resampling Methods for Networks Elizaveta Levina, University of Michigan
9:50 AM	Efficient Local Change-Point Detection for Complex Networks with Applications Shirshendu Chatterjee, City University of New York, City College; Sharmodeep Bhattacharyya, Oregon State University
10:15 AM	Floor Discussion

95 * !	Mon, 8/8/2022, 8:30 AM - 10:20 AM	CC-151A
Network Data Analysis — Topic Contributed Papers
IMS, Section on Nonparametric Statistics, International Statistical Institute
Organizer(s): Jialiang Li, National University of Singapore
Chair(s): Po-Ling Loh, University of Cambridge
8:35 AM	Graphical Continuous Lyapunov Models Niels Richard Hansen, University of Copenhagen
8:55 AM	Subsampling Based Community Detection for Large Networks Yuguo Chen, University of Illinois at Urbana-Champaign
9:15 AM	Continuous Latent Position Network Models Riccardo Rastelli, University College Dublin; Marco Corneli, Université Côte d'Azur
9:35 AM	"The Local Approach to Causal Inference Under Network Interference" Eric Auerbach, Northwestern University; Max Tabord-Meehan, University of Chicago
9:55 AM	Discussant: Jialiang Li, National University of Singapore
10:15 AM	Floor Discussion

118	Mon, 8/8/2022, 10:30 AM - 12:20 PM	CC-143B
Recent Advances in Change-Point Analysis — Invited Papers
Section on Nonparametric Statistics, Section on Statistical Learning and Data Science, IMS
Organizer(s): Xiaofeng Shao, University of Illinois at Urbana-Champaign
Chair(s): Zifeng Zhao, University of Notre Dame
10:35 AM	Nonparametric Online Change-Point Detection in High Dimensions Ali Shojaie, University of Washington
11:00 AM	Are Deviations in a Gradually Varying Mean Relevant? a Testing Approach Based on Sup-Norm Estimators Holger Dette, Ruhr University Bochum; Axel Bücher, Heinrich Heine University Düsseldorf; Florian Heinrichs, Ruhr-Universität Bochum
11:25 AM	Graph-Based Multiple Change-Point Detection Yuxuan Zhang, University of California, Davis; Hao Chen, University of California, Davis
11:50 AM	Toward Automatic Change-Point Testing and Detection in Time Series via Deep Learning Presentation Piotr Fryzlewicz, London School of Economics; Jie Li, London School of Economics; Paul Fearnhead, Lancaster University; Tengyao Wang, London School of Economics
12:15 PM	Floor Discussion

120 !	Mon, 8/8/2022, 10:30 AM - 12:20 PM	CC-102A
Recent Developments in Causal Inference — Invited Papers
IMS, Biometrics Section, ENAR
Organizer(s): Fei Xue, Purdue University
Chair(s): Fei Xue, Purdue University
10:35 AM	Energy Balancing of Covariate Distributions for Estimation of Causal Effects Jared Davis Huling, University of Minnesota; Simon Mak, Duke University
11:00 AM	Causal Inference with Invalid Instruments: Post-Selection Problems and a Solution Using Searching and Sampling Zijian Guo, Rutgers University
11:25 AM	Kernel Ordinary Differential Equations Xiaowu Dai, UC Berkeley; Lexin Li, University of California, Berkeley
11:50 AM	Randomization Inference Beyond the Sharp Null: Bounded Null Hypotheses and Quantiles of Individual Treatment Effects Xinran Li, University of Illinois at Urbana-Champaign
12:15 PM	Floor Discussion

122 *	Mon, 8/8/2022, 10:30 AM - 12:20 PM	CC-143C
Analysis of Extreme Events — Invited Papers
Section on Risk Analysis, Section on Statistics and the Environment, IMS
Organizer(s): John P Nolan, American University
Chair(s): Elena Rantou, Food and Drug Administration
10:35 AM	Extreme Value Analysis for Financial Risk Management Natalia Nolde, University of British Columbia
11:00 AM	Dependence Between Extremes of Satellite and Ground Station Precipitation Brook T Russell, Clemson University School of Mathematical and Statistical Sciences; Whitney Huang, Clemson University; Yiren T Ding, Clemson University School of Mathematical and Statistical Sciences; Jamie Dyer, Mississippi State University
11:25 AM	Statistical Frameworks to Study Climate Extremes in a Detection and Attribution Context Brian James Reich, North Carolina State University; Zun Yin, NCSU; Paula Gonzalez, Lab. des Sciences du Climat et de l'Environnement; Philippe Naveau, Laboratoire des Sciences du Climat et de l’Environnement
11:50 AM	Signal Processing in the Presence of Heavy-Tailed Extremes John P Nolan, American University
12:15 PM	Floor Discussion

178	Mon, 8/8/2022, 2:00 PM - 3:50 PM	CC-101
Memorial Session for Michael Woodroofe — Invited Papers
Memorial, Caucus for Women in Statistics, IMS, International Chinese Statistical Association
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Mary C Meyer, Colorado State University
2:05 PM	Michael Woodroofe: Statistician and Friend David Siegmund, Stanford University
2:35 PM	Beautiful Ideas, Beautiful Mind, Impact Then, Now and Future - in Memory of Woodroofe Jiayang Sun, George Mason University
3:05 PM	Michael Woodroofe: Shape Constraints and Biased Sampling Models Jon Wellner, University of Washington
3:35 PM	Floor Discussion

179 * !	Mon, 8/8/2022, 2:00 PM - 3:50 PM	CC-152B
Data Science and the Future of Statistics Organizations — Invited Panel
IMS, Royal Statistical Society, Committee on Membership Retention and Recruitment
Organizer(s): Will Eagan, Vertex Pharmaceuticals
Chair(s): Xiao-Li Meng, Harvard University
2:05 PM	Data Science and the Future of Statistical Organizations
Panelists:	David Ian Ohlssen, Novartis Liberty Vittert, Washington University in St. Louis Patrick Wolfe, Purdue University Aleksandrina Goeva, Broad Institute of MIT and Harvard Theresa Utlaut, Intel Corporation
3:40 PM	Floor Discussion

186 *	Mon, 8/8/2022, 2:00 PM - 3:50 PM	CC-203AB
Statistical Methods for Assessing Genomic Heterogeneity — Topic Contributed Papers
Section on Statistics in Genomics and Genetics, ENAR, IMS
Organizer(s): Yuchao Jiang, University of North Carolina at Chapel Hill
Chair(s): Yuchao Jiang, University of North Carolina at Chapel Hill
2:05 PM	Identifying Novel Cells in Annotating Single Cell RNA-Seq Data Ziyi Li, The University of Texas MD Anderson Cancer Center; Yizhuo Wang, The University of Texas MD Anderson Cancer Center; Kim-Anh Do , MD Anderson Cancer Center
2:25 PM	Analyzing and Comparing Multiple Spatial Gene Expression Samples with POLYspace Zhicheng Ji, Duke University; Huimin Wang, Duke University School of Medicine
2:45 PM	Scaffold: Data Generation–Based Simulation Framework for Single-Cell RNA-Seq Data Rhonda Bacher, University of Florida; Parker Knight, University of Florida; Christina Kendziorski, University of Wisconsin-Madison
3:05 PM	Exploiting Deep Transfer Learning for the Prediction of Functional Noncoding Variants Using Genomic Sequence Li Chen, Indiana University
3:25 PM	Efficient Gradient Boosting for Prognostic Biomarker Discovery Xuefeng Wang, H. Lee Moffitt Cancer Center and Research Institute
3:45 PM	Floor Discussion

191 !	Mon, 8/8/2022, 2:00 PM - 3:50 PM	CC-158AB
Misspecification and Robustness: Novel Methods and Innovative Insights — Topic Contributed Papers
International Society for Bayesian Analysis (ISBA), Section on Bayesian Statistical Science, IMS
Organizer(s): Jeffrey Miller, Harvard TH Chan School of Public Health
Chair(s): Diana Cai, Princeton University
2:05 PM	Bayesian Data Selection Eli Nathan Weinstein, Columbia University; Jeffrey Miller, Harvard TH Chan School of Public Health
2:25 PM	Robust Inference Using Posterior Bootstrap Emilia Pompe, University of Oxford
2:45 PM	Fast Approximate BayesBag Model Selection via Taylor Expansions Neil Archibald Spencer, Harvard University; Jeffrey Miller, Harvard TH Chan School of Public Health
3:05 PM	On the Robustness to Misspecification of Alpha-Posteriors and Their Variational Approximations Marco Avella Medina, Columbia University; Cynthia Rush, Columbia University; Jose Luis Montiel Olea, Columbia University; Amilcar Velez, Northwestern University
3:25 PM	Truth-Agnostic Diagnostics for Calibration Under Misspecification Jeffrey Miller, Harvard TH Chan School of Public Health; Jonathan H Huggins, Boston University
3:45 PM	Floor Discussion

201	Mon, 8/8/2022, 2:00 PM - 3:50 PM	CC-153
Estimation and Inference in Complex Systems — Contributed Papers
IMS
Chair(s): Mina Hosseini, The Janssen Pharmaceutical Companies of Johnson & Johnson
2:05 PM	An Improved Milstein Method for Numerical Solutions to Multidimensional Stochastic Differential Equations Paromita Banerjee, John Carroll University
2:20 PM	Sparse Reconstruction of Dynamical Systems with Inference Presentation Sara Venkatraman, Cornell University
2:35 PM	Sequential Common Rate Change Detection, Isolation, and Estimation in Multiple Poisson Processes Yanhong Wu, California state university, Stanislaus; Wei Biao Wu, University of Chicago
2:50 PM	A Moving (2D, 3D, 4D) Time Series Model: Predicting the Time for the Highest Gain in a Market or Business Asif Shams Adnan, East West University; Mian Arif Shams Adnan, Bowling Green State University
3:05 PM	Multivariate Nonlinear Autoregressive Time Series Model Estimation: A Semiparametric Approach Mahtab Hajebi, University of Central Florida ; S. Yaser Samadi, Southern Illinois University Carbondale
3:20 PM	Changes in a Distribuion Function Over Time Sucharita Ghosh, Swiss Federal Research Institute WSL
3:35 PM	Floor Discussion

224	Tue, 8/9/2022, 8:30 AM - 10:20 AM	CC-202A
Medallion Lecture I — Invited Papers
IMS
Organizer(s): Annie Qu, UC Irvine
Chair(s): Mike Baiocchi, Stanford University
8:35 AM	Protocols for Observational Studies: Methods and Open Problems Dylan Small, University of Pennsylvania
10:15 AM	Floor Discussion

237	Tue, 8/9/2022, 8:30 AM - 10:20 AM	CC-203AB
Graphical Models and Causality in Extremes — Topic Contributed Papers
Section on Risk Analysis, Royal Statistical Society, IMS
Organizer(s): Chen Zhou, Erasmus University Rotterdam
Chair(s): Natalia Nolde, University of British Columbia
8:35 AM	Total Positivity in Multivariate Extremes Piotr Zwiernik, University of Toronto; Frank Röttger, Université de Genève; Sebastian Engelke, Université de Genève
8:55 AM	Penalization-Based Inference for Extremal Graphical Models Presentation Michael Lalancette, University of Toronto; Sebastian Engelke, Université de Genève; Stanislav Volgushev, University of Toronto
9:15 AM	Fast Algorithm for Extreme Graphical Models Chen Zhou, Erasmus University Rotterdam; Phyllis Wan, Erasmus University Rotterdam
9:35 AM	Causal Structure Learning in Heavy-Tailed Models Nicola Gnecco, University of Geneva; Sebastian Engelke, Université de Genève; Simon Chatelain, University of Geneva; Stanislav Volgushev, University of Toronto
9:55 AM	Discussant: Sebastian Engelke, Université de Genève
10:15 AM	Floor Discussion

244	Tue, 8/9/2022, 8:30 AM - 10:20 AM	CC-204A
Advances in Statistical Machine Learning — Contributed Papers
IMS
Chair(s): Yimei Li, University of Pennsylvania
8:35 AM	Benign Overfitting Without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data Presentation Spencer Frei, University of California, Berkeley; Niladri Chatterji, Stanford University; Peter L. Bartlett, University of California, Berkeley
8:50 AM	On Well-Posedness and Minimax Optimal Rates of Nonparametric Q-Function Estimation in Off-Policy Evaluation Zhengling Qi, George Washington University
9:05 AM	Perturbation Analysis of Randomized SVD and Its Applications to High-Dimensional Statistics Yichi Zhang, North Carolina State University; Minh Tang, North Carolina State University
9:20 AM	High-Dimensional Random Forests ROLAND FIAGBE, UNIVERSITY OF CENTRAL FLORIDA
9:35 AM	Electricity Consumption Forecasting by a New Neural Network Model: Panel Semiparametric Quantile Regression Neural Network (PSQRNN) Jiangyan Wang, Nanjing Audit University; Xingcai Zhou, Nanjing Audit University; Hongxia Wang, Nanjing Audit University; Jinguan Lin, Nanjing Audit University
9:50 AM	Noise Covariance Estimation in Multi-Task High-Dimensional Linear Models Kai Tan, Rutgers University; Pierre C Bellec, Rutgers University
10:05 AM	Distribution-Free Prediction Sets Adaptive to Unknown Covariate Shift Presentation Hongxiang Qiu, University of Pennsylvania Dept of Statistics; Edgar Dobriban, University of Pennsylvania; Eric J Tchetgen Tchetgen, University of Pennsylvania

254	Tue, 8/9/2022, 10:30 AM - 12:20 PM	CC-158AB
Novel Bayesian Methods for Structural Data: Justification and Applications — Invited Papers
International Indian Statistical Association, International Society for Bayesian Analysis (ISBA), IMS
Organizer(s): Subhashis Ghoshal, North Carolina State University
Chair(s): Subhashis Ghoshal, North Carolina State University
10:35 AM	Bayesian Analysis of Multiway Data with Applications to Professional Basketball Game Analysis Weining Shen, University of California, Irvine
11:00 AM	Bayesian Analysis of Function Data Observed Over a Graph with an Application to a Daily Temperature Data Arkaprava Roy, University of Florida; Subhashis Ghoshal, North Carolina State University
11:25 AM	An Approximate Bayesian Approach to Covariate Dependent Graphical Modeling Sutanoy Dasgupta, Texas A&M University; Prasenjit Ghosh, Texas A&M University; Debdeep Pati, Texas A&M University; Bani Mallick, Texas A&M University
11:50 AM	Leveraging Low-Dimensional Structure for Efficient Gibbs Posterior Inference Ryan G Martin, North Carolina State University
12:15 PM	Floor Discussion

258 !	Tue, 8/9/2022, 10:30 AM - 12:20 PM	CC-206
On Recent Progress in Measuring Dependence and Conditional Dependence — Invited Papers
IMS, Section on Nonparametric Statistics, International Indian Statistical Association
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Bodhisattva Sen, Columbia University
10:35 AM	Measuring Association/Conditional Association on Topological Spaces Using Kernels and Geometric Graphs NABARUN DEB, Columbia University; Promit Ghosal, MIT; Bodhisattva Sen, Columbia University
11:00 AM	Recent Advances in Applying Floodgate to High-Dimensional Inference Lucas Janson, Harvard University; Lu Zhang, Harvard University
11:25 AM	On Chatterjee's Rank Correlation Fang Han, University of Washington; Zhexiao Lin, University of Washington
11:50 AM	Non-Parametric Local Causal Structure Learning Mona Azadkia, ETH Zürich ; Armeen Taeb, ETH Zürich ; Peter Bühlmann, ETH Zürich
12:15 PM	Floor Discussion

265 * !	Tue, 8/9/2022, 10:30 AM - 12:20 PM	CC-143C
Stochastic Processes in Medicine and Medical Engineering: Theoretical Foundations and Applications — Topic Contributed Papers
Section on Medical Devices and Diagnostics, IMS, Section on Physical and Engineering Sciences
Organizer(s): Jan Beran, University of Konstanz
Chair(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
10:35 AM	Functional Time Series Modeling of Mechanically Ventilated Breathing Activity Jan Beran, University of Konstanz
10:55 AM	Scalable Gaussian Process Regression for Biomedical Time-Series Data Jan Graßhoff, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering; Philipp Rostalski, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering
11:15 AM	Incorporating Model Mismatch in a Bayesian Uncertainty Quantification Analysis of a Fluid-Dynamics Model of Pulmonary Blood Circulation Presentation Mihaela Paun, University of Glasgow; Mitchel Colebank, University of California; Mette Olufsen, North Carolina State University; Nicholas Hill, University of Glasgow; Dirk Husmeier, University of Glasgow
11:35 AM	Adaptive Frequency Band Analysis for Multivariate Biomedical Time Series Scott Alan Bruce, Texas A&M University; Raanju Sundararajan, Southern Methodist University
11:55 AM	Benefits of Noise in Biomedical Research: A Multiscale Point of View Brani Vidakovic, Texas A&M University
12:15 PM	Floor Discussion

223605	Tue, 8/9/2022, 12:30 PM - 2:30 PM	M-Woodley Park
Electronic Journal of Statistics Editorial Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

223606	Tue, 8/9/2022, 12:30 PM - 2:30 PM	M-Mount Vernon Square
Annals of Statistics Editors Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director; Elyse Gustafson, Institute of Mathematical Statistics

309 !	Tue, 8/9/2022, 2:00 PM - 3:50 PM	CC-152B
Statistical Reinforcement Learning — Invited Papers
Section on Statistical Computing, Section on Statistical Learning and Data Science, IMS
Organizer(s): Will Wei Sun, Purdue University
Chair(s): Will Wei Sun, Purdue University
2:05 PM	Settling the Sample Complexity of Model-Based Offline Reinforcement Learning Presentation Yuxin Chen, Princeton University; Yuxin Chen, University of Pennsylvania; Laixi Shi, Carnegie Mellon University; Yuejie Chi, Carnegie Mellon University; Yuting Wei , University of Pennsylvania
2:30 PM	Demystifying (Deep) Reinforcement Learning with Optimism and Pessimism Zhaoran Wang, Northwestern University
2:55 PM	Doubly-Robust Estimation for an Optimal Intervention Strategy Under a Markov Decision Process Owen Leete, Duke University; Eric Laber, Duke University
3:20 PM	A Survival Reinforcement Learning Framework and Its Biomedical Applications Hunyong Cho, University of North Carolina at Chapel Hill; Shannon T. Holloway, North Carolina State University; David J. Couper, University of North Carolina, Chapel Hill; Michael Kosorok, University of North Carolina at Chapel Hill
3:45 PM	Floor Discussion

321	Tue, 8/9/2022, 2:00 PM - 3:50 PM	CC-144C
Nonparametric Inference Under Shape Constraints — Topic Contributed Papers
IMS, Section on Nonparametric Statistics, Royal Statistical Society
Organizer(s): Richard J Samworth, University of Cambridge
Chair(s): Richard J Samworth, University of Cambridge
2:05 PM	A Non-Asymptotic Framework for Approximate Message Passing in Spiked Models Presentation Yuting Wei , University of Pennsylvania
2:25 PM	Noisy Linear Inverse Problems Under Convex Constraints: Exact Risk Asymptotics in High Dimensions Qiyang Han, Rutgers University
2:45 PM	Nonparametric Tuning-Free Estimation of S-Shaped Functions Oliver Feng, University of Cambridge; Yining Chen, London School of Economics; Qiyang Han, Rutgers University; Raymond J. Carroll, Texas A&M University; Richard J Samworth, University of Cambridge
3:05 PM	Nonparametric Doubly Robust Testing for Continuous Treatment Effects via Smoothness and via Shape Constraints Charles Doss, University of Minnesota; Guangwei Weng, University of Minnesota; Lan Wang, University of Miami
3:25 PM	Convergence Rates for Estimating Multivariate Scale Mixtures of Uniform Densities Adityanand Guntuboyina, University of California Berkeley
3:45 PM	Floor Discussion

350	Tue, 8/9/2022, 2:00 PM - 3:50 PM	CC-Hall D
Contributed Poster Presentations: IMS — Contributed Poster Presentations
IMS
Chair(s): Gyuhyeong Goh, Kansas State University
41:	Fourier Method on Central Mean Subspace in Time Series Tharindu Priyan De Alwis, Southern Illinois University Carbondale ; S. Yaser Samadi, Southern Illinois University Carbondale

223583	Wed, 8/10/2022, 7:30 AM - 9:00 AM	M-L'Enfant Plaza
Statistics Surveys Editorial Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director; Elyse Gustafson, Institute of Mathematical Statistics

360 * !	Wed, 8/10/2022, 8:30 AM - 10:20 AM	CC-206
New Areas in Complex High-Dimensional Data Analysis — Invited Papers
International Indian Statistical Association, IMS, ENAR
Organizer(s): Debashis Mondal, Washington University in St. Louis
Chair(s): Debashis Mondal, Washington University in St. Louis
8:35 AM	Phylogenetically Informed Methods for Microbiome Data Analysis Julia Fukuyama, Indiana University, Bloomington
9:00 AM	Two-Sample Tests for Inhomogeneous Random Graphs Bhaswar Bhattacharya, University of Pennsylvania
9:25 AM	Scalable Estimation of Microbial Co-Occurrence Networks with Variational Autoencoders James Morton, National Institute of Child Health and Development; Justin Silverman , Pennsylvania State University; Gleb Tikhonov, University of Helsinki; Harri Lähdesmäki, University of Aalto; Richard Bonneau, Simons Foundation
9:50 AM	Multivariate, Heteroscedastic Empirical Bayes via Nonparametric Maximum Likelihood Presentation Bodhisattva Sen, Columbia University; Adityanand Guntuboyina, University of California Berkeley; Jake Soloff, University of California at Berkeley
10:15 AM	Floor Discussion

369 * !	Wed, 8/10/2022, 8:30 AM - 10:20 AM	CC-150B
Analysis of Random Objects — Invited Papers
Section on Statistical Computing, Section on Nonparametric Statistics, Section on Statistical Learning and Data Science, IMS
Organizer(s): Lingzhou Xue, Penn State University and National Institute of Statistical Sciences
Chair(s): Qi Zhang, Penn State University
8:35 AM	Partially Global Fréchet Regression Danielle C. Tucker, University of Illinois at Chicago; Yichao C. Wu, University of Illinois at Chicago
8:55 AM	Single Index Fréchet Regression Hans-Georg Müller, University of California, Davis ; Satarupa Bhattacharjee, University of California, Davis
9:15 AM	Dimension Reduction and Data Visualization for Fréchet Regression Qi Zhang, Penn State University; Lingzhou Xue, Penn State University and National Institute of Statistical Sciences; Bing Li, Penn State University
9:35 AM	Functional Models for Time-Varying Random Objects and Dynamic Networks Paromita Dubey, University of Southern California; Hans-Georg Müller, University of California, Davis
9:55 AM	Nonlinear Sufficient Dimension Reduction for Distributional Data Qi Zhang, Penn State University; Lingzhou Xue, Penn State University and National Institute of Statistical Sciences; Bing Li, Penn State University
10:15 AM	Floor Discussion

373 * !	Wed, 8/10/2022, 8:30 AM - 10:20 AM	CC-159AB
Recent Advances in Complex and High-Dimensional Data — Topic Contributed Papers
IMS, Section on Nonparametric Statistics, Section on Statistical Learning and Data Science
Organizer(s): Shuheng Zhou, University of California, Riverside
Chair(s): Min Xu, Rutgers University
8:35 AM	Differentially Private Inference via Noisy Optimization Po-Ling Loh, University of Cambridge; Marco Avella Medina, Columbia University; Casey Bradshaw, Columbia University
8:55 AM	High-Dimensional Changepoint Estimation with Heterogeneous Missingness Tengyao Wang, London School of Economics
9:15 AM	Guaranteed Functional Tensor Singular Value Decomposition Anru Zhang, Duke University; Rungang Han, Duke University; Pixu Shi, Duke University
9:35 AM	Leave-One-Out Singular Subspace Perturbation Analysis for Spectral Clustering Harrison Zhou, Yale University
9:55 AM	Concentration of Measure Bounds for Matrix-Variate Data with Missing Values Shuheng Zhou, University of California, Riverside
10:15 AM	Floor Discussion

385	Wed, 8/10/2022, 8:30 AM - 10:20 AM	CC-140A
SPEED: Statistical Methods and Applications in Medical Research, Risk Analysis, and Marketing Part 1 — Contributed Speed
Biopharmaceutical Section, Section on Medical Devices and Diagnostics, Section on Statistics in Imaging, IMS, International Chinese Statistical Association, Section on Risk Analysis, Section on Statistics in Marketing
Chair(s): Michael Higgins, Kansas State University
8:35 AM	Near Real-Time Surveillance of COVID-19 Vaccine Safety in the U.S. Food and Drug Administration Biologics Effectiveness and Safety (BEST) Initiative Data Network Mao Hu, Acumen LLC; Patricia Lloyd, US Food and Drug Administration; Cindy Ke Zhou, US Food and Drug Administration; An-Chi Lo, Acumen LLC; Yoganand Chillarige, Acumen LLC; John Hornberger, Acumen LLC; Jeffrey Kelman, Centers for Medicare & Medicaid Services; Anne Marie Kline, Aetna; Cheryl N McMahill-Walraven, Aetna; Kandace L. Amend, Optum Epidemiology; John D Seeger, Optum Epidemiology; Daniel Beachler, HealthCore, Inc.; Alex Secora, IQVIA; Christian Reich, IQVIA; Azadeh Shoaibi, US Food and Drug Administration; Hui Lee Wong, US Food and Drug Administration; Steven Anderson, US Food and Drug Administration
8:40 AM	Integration of Efficacy Biomarkers Together with Toxicity Endpoints in Immuno-Oncology Dose Finding Studies Yiding Zhang, Sanofi; Zhixing Xu, Sanofi; Ji Lin, Sanofi; Hui Quan, Sanofi
8:45 AM	Practical Implementation of Randomization in a Complex Site-Level Stepped-Wedge Cluster Pragmatic Randomized Trial Wen Wan, Section of General Internal Medicine, University of Chicago; Linda Rosul, Access community health network; Theodore Karrison, University of Chicago; Neda Laiteerapong, Section of General Internal Medicine, University of Chicago
8:50 AM	A Two-Stage Method to Minimize the Expected Sample Size of a Single-Arm Study Under the Alternative Hypothesis Xiaobo Zhong, Bristol Myers Squibb; Qian Li, Biostatistics and Strategic Consulting
8:55 AM	Improving Dose-Escalation Design with Historical and Concurrent Trial Data Abhishek Kumar Dubey, Bristol Myer Squibb; Arun Kumar Kumar, Bristol Myer Squibb; Kaushal Kumar Mishra, Bristol Myer Squibb
9:00 AM	BGLAM: A Bayesian General Logistic Autoregressive Model for Correlated Binary Outcomes Ahmad Hakeem Abdul Wahab, Janssen Pharmaceuticals; Arman Sabbaghi, Purdue University; Maggie O'Haire, Purdue University
9:05 AM	Practical Guidance on Mixture Priors Specification in Oncology Dose Escalation Models Frank Shen, Bristol Myers Squibb; Yanping Chen, Bristol Myers Squibb; Rong Liu, BMS
9:10 AM	Overlap Weight-Based Adaptive Bayesian Commensurate Prior for Augmenting the Control Arm of a Randomized Controlled Trial Yeonil Kim, Merck & Co., Inc. ; Erina Paul, Merck & Co., Inc.
9:15 AM	Power Analysis for Longitudinal Cluster Randomized Trials with Binary Outcomes Jijia Wang, UT Southwestern Medical Center
9:20 AM	Association of COVID Vaccine Hesitancy and Vaccine Misinformation Using Google Trends Analytics Vaccine Hesitancy Lan Gao, The University of Tennessee at Chattanooga
9:30 AM	Extending the Weighted Generalized Score Statistic for Comparison of Correlated Means Aaron D. Jones, Duke University; Andrzej S. Kosinski, Duke University
9:35 AM	Can Cutaneous Squamous Cell Carcinoma Be Properly Graded? Investigation of the Differentiation Grading Among Dermatopathologists Yevgeniya Gokun, The Ohio State University; Xueliang Pan, The Ohio State University; David Carr, The Ohio State University; Katie Shahwan, The Ohio State University; Jessica Nash, The Ohio State University
9:45 AM	Homogeneity Test for Ordinal ROC Regression and Application to Facial Recognition Ty Nguyen, University of Central Florida; Larry Tang, University of Central Florida
9:50 AM	Club Exco: Clustering Brain Extreme Communities from Multi-Channel EEG Data Matheus Bartolo Guerrero, King Abdullah University of Science and Technology; Raphael Huser, King Abdullah University of Science and Technology (KAUST); Hernando Ombao, King Abdullah University of Science and Technology
9:55 AM	Large-Scale Correlation Screening Under Dependence for Brain Functional Connectivity Inference Hanâ LBATH, Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK; Alexander Petersen, Brigham Young University; Sophie ACHARD, Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK
10:00 AM	Correcting Under-Reporting in Cyber Incidents Seema Sangari, Kennesaw State University; Eric Dallal, Verisk
10:05 AM	Outcome-Dependent Sampling on Posterior Estimates of Salesperson Rankings Neil Mercer, Google LLC; Frank Yoon, Google LLC; Ignacio Martinez, Google LLC
10:10 AM	A Framework for Measuring Influencer Marketing Gary Cohen, Amazon.com; Vanja Dukic, Amazon.com

10:15 AM	Floor Discussion

390	Wed, 8/10/2022, 8:30 AM - 10:20 AM	CC-155
Functional and High-Dimensional Data — Contributed Papers
IMS
Chair(s): Yaqing Chen, University of California, Davis
8:35 AM	Robust Estimation for the Function-on-Function Regression Model Ufuk Beyaztas, Marmara University; Han Lin Shang, Macquarie University; Abhijit Mandal, Univeristy of Texas at El Paso
8:50 AM	Minimax Lower Bounds in High Order Tensor Models with Applications to Neuroimaging Chitrak Banerjee, Wells Fargo N A; LYUDMILA SAKHANENKO, Michigan State University; David C Zhu, Michigan State University
9:05 AM	The Stein Effect for Frechet Means Andrew McCormack, Duke University; Peter Hoff, Duke University
9:20 AM	Sufficient Statistics in Functional Data Analysis Khalil Shafie, University of Northern Colorado; Siamak Noorbaloochi, Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care
9:35 AM	An Empirical Bayes Regression for Multi-Tissue EQTL Data Analysis Fei Xue, Purdue University; Hongzhe Lee, University of Pennsylvania
9:50 AM	Limit Distributions and Fast Rates for Sliced Wasserstein Distances Ritwik Sadhu, Department of Statistics and Data Science, Cornell University; Ziv Goldfeld, Department of Electrical and Computer Engineering, Cornell University; Kengo Kato, Department of Statistics and Data Science, Cornell University
10:05 AM	Floor Discussion

404 * !	Wed, 8/10/2022, 10:30 AM - 12:20 PM	CC-204B
Gaussian Process Models Over Non-Euclidean Domains — Invited Papers
International Society for Bayesian Analysis (ISBA), IMS, Section on Nonparametric Statistics
Organizer(s): Didong Li, Princeton University
Chair(s): Abhi Datta, Johns Hopkins University
10:35 AM	Inference for Gaussian Processes on Compact Riemannian Manifold Didong Li, Princeton University; Wenpin Tang, Columbia University; Sudipto Banerjee, UCLA
11:05 AM	Inferring Manifolds from Noisy Data Using Gaussian Processes Nan Wu, Duke University; David Dunson, Duke University
11:35 AM	Nonparametric Multi-Shape Modeling with Uncertainty Quantification Hengrui Luo, Lawrence Berkeley National Laboratory; Justin Strait, Los Alamos National Laboratory
12:05 PM	Floor Discussion

405	Wed, 8/10/2022, 10:30 AM - 12:20 PM	CC-207A
Medallion Lecture II — Invited Papers
IMS
Organizer(s): Annie Qu, UC Irvine
Chair(s): Annie Qu, UC Irvine
10:35 AM	Extreme Conditional Quantiles Huixia Wang, The George Washington University
12:15 PM	Floor Discussion

406 * !	Wed, 8/10/2022, 10:30 AM - 12:20 PM	CC-152B
Leo Breiman’s Two Cultures: Introspection, Debate, and Discussion 20 Years Later — Invited Panel
Section on Statistics in Epidemiology, ENAR, IMS
Organizer(s): Nandita Mitra, University of Pennsylvania
Chair(s): Nandita Mitra, University of Pennsylvania
10:35 AM	Leo Breiman’s Two Cultures: Introspection, Debate, and Discussion 20 Years Later
Panelists:	Mike Baiocchi, Stanford University Andrew Gelman, Columbia University Debashis Ghosh, Colorado School of Public Health Arman Oganisian, Brown University Ani Eloyan, Brown University Elizabeth Ogburn, Johns Hopkins University Anna Neufeld, University of Washington
12:10 PM	Floor Discussion

443	Wed, 8/10/2022, 10:30 AM - 11:15 AM	CC-Hall D
SPEED: Statistical Methods and Applications in Medical Research, Risk Analysis, and Marketing Part 2 — Contributed Poster Presentations
Biopharmaceutical Section, Section on Medical Devices and Diagnostics, Section on Statistics in Imaging, IMS, International Chinese Statistical Association, Section on Risk Analysis, Section on Statistics in Marketing
Chair(s): Michael Higgins, Kansas State University
01:	Near Real-Time Surveillance of COVID-19 Vaccine Safety in the U.S. Food and Drug Administration Biologics Effectiveness and Safety (BEST) Initiative Data Network Mao Hu, Acumen LLC; Patricia Lloyd, US Food and Drug Administration; Cindy Ke Zhou, US Food and Drug Administration; An-Chi Lo, Acumen LLC; Yoganand Chillarige, Acumen LLC; John Hornberger, Acumen LLC; Jeffrey Kelman, Centers for Medicare & Medicaid Services; Anne Marie Kline, Aetna; Cheryl N McMahill-Walraven, Aetna; Kandace L. Amend, Optum Epidemiology; John D Seeger, Optum Epidemiology; Daniel Beachler, HealthCore, Inc.; Alex Secora, IQVIA; Christian Reich, IQVIA; Azadeh Shoaibi, US Food and Drug Administration; Hui Lee Wong, US Food and Drug Administration; Steven Anderson, US Food and Drug Administration
02:	Dose Finding via Efficacy Biomarkers and Toxicity Endpoints in Immuno-Oncology Clinical Trials Yiding Zhang, Sanofi; Zhixing Xu, Sanofi; Ji Lin, Sanofi; Hui Quan, Sanofi
03:	Practical Implementation of Randomization in a Complex Site-Level Stepped-Wedge Cluster Pragmatic Randomized Trial Wen Wan, Section of General Internal Medicine, University of Chicago; Linda Rosul, Access community health network; Theodore Karrison, University of Chicago; Neda Laiteerapong, Section of General Internal Medicine, University of Chicago
04:	A Two-Stage Method to Minimize the Expected Sample Size of a Single-Arm Study Under the Alternative Hypothesis Xiaobo Zhong, Bristol Myers Squibb; Qian Li, Biostatistics and Strategic Consulting
05:	Improving Dose-Escalation Design with Historical and Concurrent Trial Data Abhishek Kumar Dubey, Bristol Myer Squibb; Arun Kumar Kumar, Bristol Myer Squibb; Kaushal Kumar Mishra, Bristol Myer Squibb
06:	BGLAM: A Bayesian General Logistic Autoregressive Model for Correlated Binary Outcomes Ahmad Hakeem Abdul Wahab, Janssen Pharmaceuticals; Arman Sabbaghi, Purdue University; Maggie O'Haire, Purdue University
07:	Practical Guidance on Mixture Priors Specification in Oncology Dose Escalation Models Frank Shen, Bristol Myers Squibb; Yanping Chen, Bristol Myers Squibb; Rong Liu, BMS
08:	Overlap Weight-Based Adaptive Bayesian Commensurate Prior for Augmenting the Control Arm of a Randomized Controlled Trial Yeonil Kim, Merck & Co., Inc. ; Erina Paul, Merck & Co., Inc.
09:	Power Analysis for Longitudinal Cluster Randomized Trials with Binary Outcomes Jijia Wang, UT Southwestern Medical Center
10:	Association of COVID Vaccine Hesitancy and Vaccine Misinformation Using Google Trends Analytics Vaccine Hesitancy Lan Gao, The University of Tennessee at Chattanooga
11:	Extending the Weighted Generalized Score Statistic for Comparison of Correlated Means Aaron D. Jones, Duke University; Andrzej S. Kosinski, Duke University
12:	Can Cutaneous Squamous Cell Carcinoma Be Properly Graded? Investigation of the Differentiation Grading Among Dermatopathologists Yevgeniya Gokun, The Ohio State University; Xueliang Pan, The Ohio State University; David Carr, The Ohio State University; Katie Shahwan, The Ohio State University; Jessica Nash, The Ohio State University
13:	Evaluation of Patient-Reported Outcomes Using Kappa Statistics Saryet Kucukemiroglu, Food and Drug Administration; Manasi Sheth, Food and Drug Administration
14:	Statistical Considerations When Evaluating Diagnostic Devices with Categorical Output Manasi Sheth, Food and Drug Administration
15:	Homogeneity Test for Ordinal ROC Regression and Application to Facial Recognition Ty Nguyen, University of Central Florida; Larry Tang, University of Central Florida
16:	Club Exco: Clustering Brain Extreme Communities from Multi-Channel EEG Data Matheus Bartolo Guerrero, King Abdullah University of Science and Technology; Raphael Huser, King Abdullah University of Science and Technology (KAUST); Hernando Ombao, King Abdullah University of Science and Technology
17:	Large-Scale Correlation Screening Under Dependence for Brain Functional Connectivity Inference Hanâ LBATH, Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK; Alexander Petersen, Brigham Young University; Sophie ACHARD, Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK
18:	Correcting Under-Reporting in Cyber Incidents Seema Sangari, Kennesaw State University; Eric Dallal, Verisk
19:	Outcome-Dependent Sampling on Posterior Estimates of Salesperson Rankings Neil Mercer, Google LLC; Frank Yoon, Google LLC; Ignacio Martinez, Google LLC
20:	A Framework for Measuring Influencer Marketing Gary Cohen, Amazon.com; Vanja Dukic, Amazon.com

457 * !	Wed, 8/10/2022, 2:00 PM - 3:50 PM	CC-151B
Conformal Prediction, Semiparametric Statistics, and Causal Inference — Invited Papers
IMS, Section on Nonparametric Statistics
Organizer(s): Arun K Kuchibhotla, Carnegie Mellon University; Eric J Tchetgen Tchetgen, University of Pennsylvania; Yachong Yang, University of Pennsylvania
Chair(s): Oliver Dukes, University of Pennsylvania
2:05 PM	Conformal Inference of Counterfactuals and Individual Treatment Effects Lihua Lei, Stanford University; Emmanuel Candès, Stanford University
2:25 PM	Inference for Sensitivity Parameters in Causal Inference Larry Wasserman, Carnegie Mellon University
2:45 PM	Doubly Robust Prediction Under Covariate Shift Yachong Yang, University of Pennsylvania; Eric J Tchetgen Tchetgen, University of Pennsylvania; Arun K Kuchibhotla, Carnegie Mellon University
3:05 PM	Testing the Stability of a Black Box Algorithm Byol Kim, University of Washington; Rina Foygel Barber, University of Chicago
3:25 PM	Discussant: James M Robins, Harvard University
3:45 PM	Floor Discussion

471 !	Wed, 8/10/2022, 2:00 PM - 3:50 PM	CC-154A
New Frontier in Developments of Complex-Structured High-Dimensional Data Analysis — Topic Contributed Papers
International Chinese Statistical Association, IMS, Section on Statistics and Data Science Education
Organizer(s): Chenlu Ke, Virginia Commonwealth University; Jiaying Weng, Bentley University
Chair(s): Chenlu Ke, Virginia Commonwealth University
2:05 PM	Functional Group Lasso with Functional Predictor Selection Jun Song, Korea University; Ali Mahzarnia, UNC Charlotte
2:25 PM	Testing the Linear Mean and Constant Variance Conditions in Sufficient Dimension Reduction Yuexiao Dong, Temple University
2:45 PM	Pseudo Sufficient Dimension Reduction with Ill-Conditioned Sample Covariance Matrix Wenbo Wu, The University of Texas at San Antonio
3:05 PM	Subspace Estimation with Automatic Dimension and Variable Selection in Sufficient Dimension Reduction Jing Zeng, Florida State University; Qing Mai, Florida State University; Xin Zhang, Florida State University
3:25 PM	Triply Robust Surrogate-and-Model-Assisted Semi-Supervised Transfer Learning Mengyan Li, Bentley University; Tianxi Cai , Harvard University ; Molei Liu, Harvard University
3:45 PM	Floor Discussion

504 !	Thu, 8/11/2022, 8:30 AM - 10:20 AM	CC-144C
Computational Challenges in Modern Statistical Inference — Invited Papers
IMS, Section on Statistical Learning and Data Science, IEEE Computer Society
Organizer(s): Anru Zhang, Duke University
Chair(s): Anru Zhang, Duke University
8:35 AM	Testing Network Correlation Efficiently via Counting Trees Presentation Cheng Mao, Georgia Institute of Technology; Yihong Wu, Yale University; Jiaming Xu, Duke University; Sophie H. Yu, Duke University
9:00 AM	High-Dimensional Discriminant Analysis on Latent Variables Marten Wegkamp, Cornell University; Xin Bing, University of Toronto; Florentina Bunea, Cornell University
9:25 AM	Statistics Meets Optimization: Sharp Time-Data Tradeoffs for Iterative Algorithms in Random Nonconvex Programs Ashwin Pananjady, Georgia Tech
9:50 AM	Low-Rank Matrix Estimation with Groupwise Heteroskedasticity Galen Reeves, Duke University
10:15 AM	Floor Discussion

509 * !	Thu, 8/11/2022, 8:30 AM - 10:20 AM	CC-143A
Recent Advances in High-Dimensional Time Series Analysis — Topic Contributed Papers
Business and Economic Statistics Section, IMS, Section on Statistical Learning and Data Science
Organizer(s): S. Yaser Samadi, Southern Illinois University Carbondale
Chair(s): Ali Shojaie, University of Washington
8:35 AM	Fast, Optimal, and Targeted Predictions Using Parametrized Decision Analysis Daniel Kowal, Rice University
8:55 AM	Dimension Reduction for Vector Autoregressive Models S. Yaser Samadi, Southern Illinois University Carbondale; H. M. Wiranthe Bandara Herath, Southern Illinois University Carbondale
9:15 AM	Inference for Location of Change Points in High-Dimensional Non-Stationary Vector Auto-Regressive Models Abolfazl Safikhani, University of Florida; Abhishek Kaul, Washington State University; Yue Bai, University of Florida
9:35 AM	Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data Ruey Tsay, University of Chicgao; Zhaoxing Gao, Zhejiang University
9:55 AM	Floor Discussion

533 !	Thu, 8/11/2022, 10:30 AM - 12:20 PM	CC-207A
Prediction and Inference in Statistical Machine Learning — Invited Papers
IMS, Royal Statistical Society, ENAR
Organizer(s): Tracy Ke, Harvard University
Chair(s): Lucas Janson, Harvard University
10:35 AM	Statistical Inference After Adaptive Sampling for Longitudinal Data Kelly Wang Zhang, Harvard University; Lucas Janson, Harvard University; Susan Murphy, Harvard University
11:00 AM	Optimal Estimation of Network Mixed Memberships Tracy Ke, Harvard University
11:25 AM	WITHDRAWN Adaptive Conformal Inference Under Distribution Shift Emmanuel Candès, Stanford University; Isaac Gibbs, Stanford University
11:50 AM	Understanding Deep Q-Learning Jianqing Fan, Princeton University; Zhaoran Wang, Northwestern University; Yuchen Xie, Northwestern University; Zhuoran Yang, Yale University
12:15 PM	Floor Discussion

542 * !	Thu, 8/11/2022, 10:30 AM - 12:20 PM	CC-204B
Advances in Topological and Geometric Data Analysis — Topic Contributed Papers
IMS, Section on Statistics in Imaging, Section on Statistical Learning and Data Science
Organizer(s): Yen-Chi Chen, University of Washington; Justin Strait, Los Alamos National Laboratory
Chair(s): Yen-Chi Chen, University of Washington
10:35 AM	Methods for Testing Distributional Assumptions for Object Data Leif Ellingson, Texas Tech University; Dong Xu, Suzhou University
10:55 AM	Random Persistence Diagram Generation and Materials Vasileios Maroulas, University of Tennesse, Knoxville; Theodore Papamarkou, The University of Manchester; Farzana Nasrin, University of Hawaii; Minh Quang Le, University of Tennesse, Knoxville
11:15 AM	Density-Based Classification in Diabetic Retinopathy Through Thickness of Retinal Layers from Optical Coherence Tomography Shariq Mohammed, Boston University; Tingyang Li, University of Michigan; Xing Chen, University of Michigan; Elisa Warner, University of Michigan; Anand Shankar, University of Michigan; Maria Fernanda Abalem, University of Michigan; Thiran Jayasundera, University of Michigan; Thomas Gardner, University of Michigan; Arvind Rao, University of Michigan
11:35 AM	Featurization of Topological Data Analysis Using Persistence Landscape and Circular Coordinates Jisu Kim, Inria; Kwangho Kim, Harvard; Manzil Zaheer, Google Research; Joon Sik Kim, Carnegie Mellon University; Frédéric Chazal, Inria; Larry Wasserman, Carnegie Mellon University; Hengrui Luo, Lawrence Berkeley National Laboratory; Alice Patania, Indiana University; Mikael Vejdemo-Johansson, CUNY
11:55 AM	Discussant: Justin Strait, Los Alamos National Laboratory
12:15 PM	Floor Discussion

545 !	Thu, 8/11/2022, 10:30 AM - 12:20 PM	CC-154A
Statistical Advances in Learning Large-Scale Networks from Massive Data Sets — Topic Contributed Papers
Section on Statistical Learning and Data Science, Section on Nonparametric Statistics, IMS
Organizer(s): Lili Zheng, Rice University
Chair(s): Genevera Allen, Rice University
10:35 AM	Learning Point Process Network Models with Timing Uncertainty Yao Xie, Georgia Institute of Technology; Xiuyuan Cheng, Duke University; Tingnan Gong, Georgia Institute of Technology
10:55 AM	Statistical Inference for Networks of High-Dimensional Point Processes Mladen Kolar, The University of Chicago ; Xu Wang, University of Washington; Ali Shojaie, University of Washington
11:15 AM	Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes Presentation Lili Zheng, Rice University; Genevera Allen, Rice University
11:35 AM	Learning Latent Causal Graphs via Mixture Oracles Pradeep Ravikumar, Carnegie Mellon University
11:55 AM	Frequency-Domain Graphical Modeling of Large-Scale Time Series Sumanta Basu, Cornell University; Navonil Deb, Cornell University
12:15 PM	Floor Discussion

JSM 2022 Conference Program

Activity Details

American Statistical Association