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All Times EDT

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

Activity Details


2 * !
Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-202A
Emerging Methods in Quantum Computing, Quantum Information, and Quantum Statistical Learning — Invited Papers
Section on Statistical Computing, Section on Statistical Learning and Data Science, Section on Statistics and Data Science Education
Organizer(s): Ping Ma, University of Georgia
Chair(s): Ping Ma, University of Georgia
2:05 PM Wavelet Matrix Operations and Quantum Transforms
Zhiguo Zhang, University of Electronic Science and Technology of China; Mark Kon, Boston University
2:35 PM Statistical Computing Meets Quantum Computing
Wenxuan Zhong, University of Georgia; Yuan Ke, University of Georgia; Ping Ma, University of Georgia
3:05 PM The Role of Statistics in Quantum Computation and Quantum Information
Yazhen Wang, University of Wisconsin-Madison
3:25 PM Floor Discussion
 
 

23 * !
Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-204B
Statistical Considerations for Epidemiologic Studies of Radiation Risk — Topic Contributed Papers
Section on Statistics in Epidemiology, Committee on Applied Statisticians, Section on Statistical Computing
Organizer(s): Ashley P Golden, Oak Ridge Associated Universities
Chair(s): Isaf Al-Nabulsi, US Department of Energy
2:05 PM Excess Relative Risk and Excess Absolute Rate Models in (Radiation) Dose-Response Modeling
Dale L. Preston, Hirosoft International, Eureka, CA; Daniel O. Stram, Keck School of Medicine, University of Southern California
2:25 PM Incorporation of Dosimetric Uncertainty into Epidemiologic Calculations of Radiation Risk
Daniel O. Stram, Keck School of Medicine, University of Southern California; Dale L. Preston, Hirosoft International, Eureka, CA
2:45 PM Statistical Analysis of Atomic Bomb Survivor Data: Challenges and Opportunities
Benjamin French, Vanderbilt University Medical Center
3:05 PM Evaluation of Sources of Bias in Time-Dependent Radiation Dose Response Models for Individual Cohorts and Challenges Associated with Pooling in the Million Worker Study
Ashley P Golden, Oak Ridge Associated Universities; Sara Howard, Oak Ridge Institute for Science and Education; Benjamin French, Vanderbilt University Medical Center; Yeji Ko, Vanderbilt University
3:25 PM Availability of Epidemiological Data for Statistical Research and Classroom Instruction from the Comprehensive Epidemiologic Data Resource and Radiation Effects Research Foundation
Sara Howard, Oak Ridge Institute for Science and Education
3:45 PM Floor Discussion
 
 

24 * !
Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-154A
High-Performance Statistical Computing: Current Trends and Future Prospects — Topic Contributed Panel
Section on Statistical Computing, Section on Statistical Learning and Data Science, Section on Physical and Engineering Sciences
Organizer(s): Sameh Abdulah, KAUST
Chair(s): Sameh Abdulah, KAUST
2:05 PM High-Performance Statistical Computing: Current Trends and Future Prospects
Panelists: Marc Genton, KAUST
Dorit Hammerling, Colorado School of Mines
Zhengqing Ouyang, University of Massachusetts, Amherst
George Ostrouchov, ORNL
Hatem Ltaief, KAUST
3:40 PM Floor Discussion
 
 

28
Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-140B
SPEED: Statistical Computing and Statistics in Genomics Part 1 — Contributed Speed
Section on Statistical Computing, Section for Statistical Programmers and Analysts, Section on Statistical Graphics, Section on Statistics in Genomics and Genetics
Chair(s): Perla Reyes, Kansas State Universtiy
2:05 PM Racial Disparity in County-Level Low-Income Job Loss Rate During the COVID-19 Pandemic
Zhenyu Xu, University of Connecticut; Anthony Zeimbekakis, University of Connecticut; Jun Yan, University of Connecticut
2:10 PM Using the MiniMax Statistic to Integrate Partially Matched Multi-Omics Data
Gabriel J. Odom, Florida International University; Antonio Colaprico, University of Miami; Tiago Silva, University of Miami; Xi Steven Chen, University of miami; Lily Wang, University of Miami
2:15 PM Bayesian Hyperbolic Multi-Dimensional Scaling
Bolun Liu, Departments of Statistics, University of Washington; Tyler McCormick, University of Washington; Adrian E. Raftery, University of Washington; Shane Lubold, University of Washington
2:20 PM Correlation Testing for Inhomogeneous Random Graphs
Yukun Song, North Carolina State University; Minh Tang, North Carolina State University
2:25 PM High-Dimensional Nonlinear Spatio-Temporal Filtering Using Hierarchical Sparse Cholesky Factors
Anirban Chakraborty, Texas A&M University; Matthias Katzfuss, Texas A&M University
2:30 PM Functional Priors for Bayesian Deep Learning
Ba-Hien Tran, EURECOM; Simone Rossi, EURECOM; Dimitrios Milios, EURECOM; Pietro Michiardi, EURECOM; Maurizio Filippone, EURECOM
2:35 PM Uncertainty in Regridding for Statistical Downscaling of Solar Radiation
Maggie Bailey, Colorado School of Mines; Soutir Bandyopadhyay, Colorado School of Mines; Douglas Nychka, Colorado School of Mines
2:40 PM Using Krylov Subspace Methods for Large Scale Image Source Separation
Simon P Wilson, Trinity College Dublin; Dung P Pham, Trinity College Dublin; Kirk P Soodhalter, Trinity College Dublin
2:45 PM Visualizing Bivariate Statistics Using Ellipses Over a Scatter Plot
Jyotirmoy Sarkar, Indiana University-Purdue University Indianapolis; Mamunur Rashid, DePauw University; Siddhanta Phuyal, DePauw University
2:50 PM Bioinformatic Investigation of Zic Family of Transcription Factors in the Mature Cerebellum
Melyssa S Minto, Duke University
3:00 PM Finding Significant Communities in Cross-Correlation Networks Derived from Multi-View Data
Miheer Ulhas Dewaskar, Duke University
3:05 PM Detection of Fine-Scale Population Structure in Genetic Summary Data with Summix
Adelle Price, University of Colorado Denver; Katie Marker, University of Colorado Anschutz Medical Campus; Audrey Hendricks, University of Colorado Denver
3:10 PM A New Functional F-Statistic for Gene-Based Inference Involving Multiple Phenotypes
Adam Joseph Dugan, 23andMe, Inc.; Olga Vsevolozhskaya, University of Kentucky
3:15 PM Novel Taxa-Specific Normalization Method for Microbiome Sequencing Count Data
Ziyue Wang, NIH/National Institute of Environmental Health Sciences; Alison Motsinger-Reif, NIH/National Institute of Environmental Health Sciences; Shanshan Zhao, NIH/ National Institute of Environmental Health Sciences
3:20 PM Adjusting for Covariates in the Visualization of High-Dimensional Data
Angela Zhang, University of Washington; Michael C. Wu, Fred Hutchinson Cancer Research Center
3:25 PM Flexible Non-Parametric Tests of Sample Exchangeability and Feature Independence
Alan Aw, University of California, Berkeley; Yun Song, University of California, Berkeley; Jeffrey Spence, Stanford University
3:30 PM Demographic Profile and Factors of Homeownership Disparity in the United States
Rachel Richardson, Pacific Northwest National Laboratory - Battelle; David Degnan, Pacific Northwest National Laboratory - Battelle; Anastasiya Prymolenna, Pacific Northwest National Laboratory - Battelle; Natalie Winans, Pacific Northwest National Laboratory - Battelle; Lisa Bramer, Pacific Northwest National Laboratory - Battelle
3:35 PM An Analysis on the Impact of Socioeconomic Status on Success in School
Alyson Everett, Miami University; Thomas Fisher, The University of Miami - Ohio
3:40 PM Floor Discussion
 
 

39 * !
Sun, 8/7/2022, 4:00 PM - 5:50 PM CC-206
Advances in Time Series: Statistics Meets Machine Learning — Invited Papers
Section on Statistical Computing, Section on Nonparametric Statistics, Business and Economic Statistics Section
Organizer(s): Piotr Fryzlewicz, London School of Economics
Chair(s): Piotr Fryzlewicz, London School of Economics
4:05 PM Spectral Nonlinear Granger Causality for Multivariate Time Series
Hernando Ombao, King Abdullah University of Science and Technology; Archishman Biswas, King Abdullah University of Science and Technology
4:30 PM Asynchronous MCMC
Yves Atchade, Boston Univeristy
4:55 PM Curriculum Learning in Deep Neural Networks for Financial Forecasting
Allison Koenecke, Cornell University; Amita Gajewar, Microsoft
5:20 PM Blind Source Separation Over Space
QIWEI YAO, London School of Economics
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
 
 

56 * !
Sun, 8/7/2022, 4:00 PM - 5:50 PM CC-143A
Modern Bayesian Methods for Complex Spatial Data — Topic Contributed Papers
International Society for Bayesian Analysis (ISBA), Section on Bayesian Statistical Science, Section on Statistical Computing
Organizer(s): Aritra Halder, University of Virginia; Shariq Mohammed, Boston University
Chair(s): Shariq Mohammed, Boston University
4:05 PM Curvature Processes: Directional Concavity in Gaussian Random Fields
Aritra Halder, University of Virginia
4:25 PM Beyond Gaussian Processes: Flexible Bayesian Modeling and Inference for Geostatistical Processes
Marcos Oliveira Prates, Universidade Federal de Minas Gerais; Guilherme Aparecido Santos Aguilar, Universidade Federal de Minas Gerais; Flávio Bambirra Gonçalves, Universidade Federal de Minas Gerais
4:45 PM Covariate-Dependent Spatial Ensemble Modeling for Estimating Ambient Air Pollution Concentrations
Howard Chang, Emory University
5:05 PM Spatial Factor Models for High-Dimensional Binary Data Across Large Spatial Domains: A Case Study on Breeding Birds in the United States
Jeffrey W. Doser, Michigan State University; Andrew O. Finley, Michigan State University; Sudipto Banerjee, UCLA
5:25 PM Floor Discussion
 
 

65 * !
Sun, 8/7/2022, 4:00 PM - 5:50 PM CC-204A
Computational Challenges in Software and Algorithms — Contributed Papers
Section on Statistical Computing
Chair(s): Kaiqiong Zhao, University of Alberta
4:05 PM Writing R Extensions in Rust
David B. Dahl, Brigham Young University
4:20 PM Simplified Simulations with the Simitation Package for R
David Shilane, Columbia University
4:35 PM Multimultiv, a Package for Parameter Estimation of Multi-Level Multivariate Data
Michael Terry Anderson, University of Texas at San Antonio; Anuradha Roy, University of Texas at San Antonio
4:50 PM Machine Learning for Multivariate Time Series with the R Package Mlmts
Ángel López-Oriona, University of A Coruña; José A. Vilar, University of A Coruña
5:05 PM NeuCA: A Neural Network-Based Cell Annotation Method with Web-App and GUI
Ziyi Li, The University of Texas MD Anderson Cancer Center; Hao Feng, Case Western Reserve University
5:20 PM CUR Algorithm for Data Analysis
Kathryn Linehan, University of Virginia, Biocomplexity Institute, Social and Decision Analytics Division; Radu Balan, University of Maryland, Dept of Mathematics & Center for Sci Computation and Math Modeling
5:35 PM Floor Discussion
 
 

73
Sun, 8/7/2022, 5:05 PM - 5:50 PM CC-Hall D
SPEED: Statistical Computing and Statistics in Genomics Part 2 — Contributed Poster Presentations
Section on Statistical Computing, Section for Statistical Programmers and Analysts, Section on Statistical Graphics, Section on Statistics in Genomics and Genetics
Chair(s): Perla Reyes, Kansas State Universtiy
01: Racial Disparity in County-Level Low-Income Job Loss Rate During the COVID-19 Pandemic
Zhenyu Xu, University of Connecticut; Anthony Zeimbekakis, University of Connecticut; Jun Yan, University of Connecticut
02: Using the MiniMax Statistic to Integrate Partially Matched Multi-Omics Data
Gabriel J. Odom, Florida International University; Antonio Colaprico, University of Miami; Tiago Silva, University of Miami; Xi Steven Chen, University of miami; Lily Wang, University of Miami
03: Bayesian Hyperbolic Multi-Dimensional Scaling
Bolun Liu, Departments of Statistics, University of Washington; Tyler McCormick, University of Washington; Adrian E. Raftery, University of Washington; Shane Lubold, University of Washington
04: Correlation Testing for Inhomogeneous Random Graphs
Yukun Song, North Carolina State University; Minh Tang, North Carolina State University
05: High-Dimensional Nonlinear Spatio-Temporal Filtering Using Hierarchical Sparse Cholesky Factors
Anirban Chakraborty, Texas A&M University; Matthias Katzfuss, Texas A&M University
06: Functional Priors for Bayesian Deep Learning
Ba-Hien Tran, EURECOM; Simone Rossi, EURECOM; Dimitrios Milios, EURECOM; Pietro Michiardi, EURECOM; Maurizio Filippone, EURECOM
07: Uncertainty in Regridding for Statistical Downscaling of Solar Radiation
Maggie Bailey, Colorado School of Mines; Soutir Bandyopadhyay, Colorado School of Mines; Douglas Nychka, Colorado School of Mines
08: Using Krylov Subspace Methods for Large Scale Image Source Separation
Simon P Wilson, Trinity College Dublin; Dung P Pham, Trinity College Dublin; Kirk P Soodhalter, Trinity College Dublin
09: Visualizing Bivariate Statistics Using Ellipses Over a Scatter Plot
Jyotirmoy Sarkar, Indiana University-Purdue University Indianapolis; Mamunur Rashid, DePauw University; Siddhanta Phuyal, DePauw University
10: Bioinformatic Investigation of Zic Family of Transcription Factors in the Mature Cerebellum
Melyssa S Minto, Duke University
11: Finding Significant Communities in Cross-Correlation Networks Derived from Multi-View Data
Miheer Ulhas Dewaskar, Duke University
12: Detection of Fine-Scale Population Structure in Genetic Summary Data with Summix
Adelle Price, University of Colorado Denver; Katie Marker, University of Colorado Anschutz Medical Campus; Audrey Hendricks, University of Colorado Denver
13: A New Functional F-Statistic for Gene-Based Inference Involving Multiple Phenotypes
Adam Joseph Dugan, 23andMe, Inc.; Olga Vsevolozhskaya, University of Kentucky
14: Novel Taxa-Specific Normalization Method for Microbiome Sequencing Count Data
Ziyue Wang, NIH/National Institute of Environmental Health Sciences; Alison Motsinger-Reif, NIH/National Institute of Environmental Health Sciences; Shanshan Zhao, NIH/ National Institute of Environmental Health Sciences
15: Adjusting for Covariates in the Visualization of High-Dimensional Data
Angela Zhang, University of Washington; Michael C. Wu, Fred Hutchinson Cancer Research Center
16: Flexible Non-Parametric Tests of Sample Exchangeability and Feature Independence
Alan Aw, University of California, Berkeley; Yun Song, University of California, Berkeley; Jeffrey Spence, Stanford University
17: Demographic Profile and Factors of Homeownership Disparity in the United States
Rachel Richardson, Pacific Northwest National Laboratory - Battelle; David Degnan, Pacific Northwest National Laboratory - Battelle; Anastasiya Prymolenna, Pacific Northwest National Laboratory - Battelle; Natalie Winans, Pacific Northwest National Laboratory - Battelle; Lisa Bramer, Pacific Northwest National Laboratory - Battelle
18: An Analysis on the Impact of Socioeconomic Status on Success in School
Alyson Everett, Miami University; Thomas Fisher, The University of Miami - Ohio
 
 

97 * !
Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-149AB
New Methods for Structured Variable Selection — Topic Contributed Papers
SSC (Statistical Society of Canada), ENAR, Section on Statistical Computing
Organizer(s): Mireille Elisa Schnitzer, Universite de Montreal; Guanbo Wang, McGill University
Chair(s): Mireille Elisa Schnitzer, Universite de Montreal
8:35 AM A General Framework for Identification of Permissible Variable Subsets in Structured Model Selection Presentation
Guanbo Wang, McGill University; Mireille Elisa Schnitzer, Universite de Montreal; Tom Chen, Harvard Pilgrim Health Care Institute and Harvard Medical School; Rui Wang, Harvard T.H. Chan School of Public Health; Robert William Platt, McGill University
8:55 AM Leveraging the Predictor Structure with a Doubly Sparse Penalty Function to Improve Outcome Prediction and Relevant Predictor Identification
Matthew Stephenson, University of New Brunswick - Saint John; Ayesha Ali, University of Guelph; Gerarda Darlington, University of Guelph
9:15 AM Flexible Regularized Estimating Equations: Some New Perspectives
Yi Yang, McGill University
9:35 AM Variable Selection in High-Dimensional Linear Regression Accounting for Heterogeneity in Covariate Effects Across Multiple Data Sources
Tingting Yu, Harvard Pilgrim Health Care Institute and Harvard Medical School
9:55 AM Canonical Correlation Analysis in High Dimensions with Structured Regularization
Elena Tuzhilina, Stanford University; Leonardo Tozzi, Stanford University; Trevor Hastie, Stanford University
10:15 AM Floor Discussion
 
 

98
Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-159AB
Student Paper Award and John M. Chambers Statistical Software Award — Topic Contributed Papers
Section on Statistical Graphics, Section on Statistical Computing
Organizer(s): Raymond K. W. Wong, Texas A&M University
Chair(s): Inyoung Kim, Virginia Tech
8:35 AM Core-Elements for Least Squares Estimation
Mengyu Li, Renmin University of China; Cheng Meng, Renmin University of China
8:55 AM Eye Fitting Straight Lines in the Modern Era
Emily A. Robinson, University of Nebraska - Lincoln; Susan VanderPlas, University of Nebraska - Lincoln; Reka Howard, University of Nebraska - Lincoln
9:15 AM Distribution Compression in Near-Linear Time
Abhishek Shetty, University of California Berkeley; Raaz Dwivedi, MIT; Lester Mackey, Microsoft Research New England
9:35 AM Bag of Little Bootstraps for Massive and Distributed Longitudinal Data
Xinkai Zhou, UCLA; Jin Zhou, UCLA; Hua Zhou, UCLA
9:55 AM dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python Presentation
Hubert Baniecki, Warsaw University of Technology
10:15 AM Floor Discussion
 
 

107
Mon, 8/8/2022, 8:30 AM - 10:20 PM CC-140A
SPEED: Statistical Methods, Computing, and Applications Part 1 — Contributed Speed
International Society for Bayesian Analysis (ISBA), Section on Nonparametric Statistics, Section on Physical and Engineering Sciences, Section on Statistical Computing, Section on Statistics in Defense and National Security, Section on Statistics in Genomics and Genetics, WNAR
Chair(s): Rui Xie, University of Central Florida
8:35 AM The Role of Berkson Paradox in Significance Testing
Miodrag Lovric, Radford University
8:40 AM The growclusters Package for R
Randall Powers, Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics; Terrance D Savitsky, U.S. Bureau of Labor Statistics
8:45 AM Analysis of Accelerometer Data from NHANES Database Using Fréchet Single Index Model
Aritra Ghosal , University of California, Santa Barbara ; Wendy Meiring , University of California Santa Barbara ; Alexander Petersen, Brigham Young University; Marcos Matabuena , University of Santiago de Compostela
8:50 AM Double Sampling for Informative Coarsening: Considerations for Bias Reduction and Efficiency Gain
Alex Levis, Harvard T.H. Chan School of Public Health; Rajarshi Mukherjee, Harvard T.H. Chan School of Public Health; Rui Wang, Harvard T.H. Chan School of Public Health; Sebastien Haneuse, Harvard T.H. Chan School of Public Health
8:55 AM Double Machine Learning in a Semiparametric Approach: An Innovative Causal Inference for Observational Studies
Lynda Aouar, University of Northern Colorado
9:00 AM A Comparison of Regression Discontinuity Effect Estimation for Small Samples
Daryl Swartzentruber, The Ohio State University; Eloise E Kaizar, The Ohio State University
9:05 AM Reliability for Binary and Ordinal Data in Forensics
Hina Arora, University of California Irvine; Naomi Kaplan-Damary, Hebrew University; Hal S. Stern, University of California-Irvine
9:10 AM Approaching Supersaturated Screening as a Pilot Experiment
Michael McKibben, NCSU; Jonathan Stallrich, North Carolina State University
9:15 AM Bayesian Modeling of Spatial Molecular Profiling Data at the Single-Cell Level
Jie Yang, The University of Texas at Dallas; Sunyoung Shin, University of Texas at Dallas; Qiwei Li, The University of Texas at Dallas
9:20 AM W-BETEL: Bayesian Exponentially Tilted Empirical Likelihood with Parametric Restriction via a Modified Wasserstein Metric
Abhisek Chakraborty, Texas A & M University; Anirban Bhattacharya, Texas A&M University; Debdeep Pati, Texas A&M University
9:30 AM Interpretable Modeling of Genotype-Phenotype Landscapes with State-of-the-Art Predictive Power
Peter Tonner, National Institute of Standards and Technology; David Ross, National Institute of Standards and Technology; Abe Pressman, National Institute of Standards and Technology
9:35 AM Cybersecurity and Infrastructure Security Agency Enterprise Conceptual Data Model
Swami Natarajan, The MITRE Corporation
9:40 AM MCMC-CE: A Novel Approach for Accurate Estimation of the Distributions of Large Quadratic Forms of Normal Variables
Bich Na Choi, Medical College of Georgia, Augusta University; Yang Shi, Augusta University
9:50 AM Bayesian Iterative Conditional Stochastic Search (BICOSS) for GWAS
Jacob Williams, Virginia Polytechnic Institute and State University; Marco Ferreira, Virginia Tech
9:55 AM A Statistical Framework for Deepfake Detection
Shannon Gallagher, Software Engineering Institute, Carnegie Mellon University; Catherine Bernaciak, Software Engineering Institute, Carnegie Mellon University; Jeffrey Mellon, Software Engineering Institute, Carnegie Mellon University; Dominic Ross, Software Engineering Institute, Carnegie Mellon University
10:00 AM Developing Logistic Regression for the High-Dimensional DNA Methylation Data
Mohamed salem Milad, Arkansas State University
10:05 AM A Survey of Likelihood Ratio Method Development and Implementation AcrossMultiple Forensic Disciplines
Lulu Chen, University of Central Florida; Larry Tang, University of Central Florida; Jonathon Phillips, National Institute of Standards and Technology
10:10 AM Modeling Sparse Data Using MLE with Applications to Microbiome Data
Hani Aldirawi, California State University San Bernardino
10:15 AM Floor Discussion
 
 

113
Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-142
Statistical Computing in Modern Statistics — Contributed Papers
Section on Statistical Computing
Chair(s): Si Cheng, University of Washington
8:35 AM Conditional Distributions of Statistics and Other Inferential Procedures in States of Hidden Sparse Markov Models
Donald E.K. Martin, North Carolina State University; Iris Bennett, Corteva Agroscience
8:50 AM General Gamma-Based Copulas with Applications in Tail Dependence
Matthew Arvanitis, USDA Forest Products Laboratory; Barry C Arnold, UC Riverside
9:05 AM Salary Determination Using Skill Profiles and Work Experience for the Skilled Technical Workforce
Cesar Montalvo, University of Virginia; Leonel Siwe, University of Virginia; Haleigh Tomlin, Washington and Lee University; Vicki Lancaster, University of Virginia
9:20 AM Some Generalized Regression Models and Bayesian Based Feature Extractions for Several Mixture Probabilistic Models
M Shamsuddin, Dhaka; Mian Arif Shams Adnan, Bowling Green State University
9:35 AM Change Point in Variance of Long-Range Dependent Processes
Kyungduk Ko, Boise State University
9:50 AM Floor Discussion
 
 

126 * !
Mon, 8/8/2022, 10:30 AM - 12:20 PM CC-101
Topics at the Frontier of Statistical Computing and Machine Learning — Invited Papers
Section on Bayesian Statistical Science, Section on Statistical Computing, Section on Statistical Learning and Data Science
Organizer(s): Robert Kohn, University of New South Wales
Chair(s): Hung Dao, University of New South Wales
10:35 AM Flexible Variational Bayes Based on a Copula of a Mixture of Normals
Robert Kohn, University of New South Wales; David Gunawan, School of Mathematics and Applied Statistics; David Nott, University of Singapore
11:05 AM Variational Bayes on Manifolds
Minh-Ngoc Tran, University of Sydney; Dang Nguyen, University of Alabama; Duy Nguyen, Marist College
11:35 AM Sparse Hamiltonian Flows (Or Bayesian Coresets Without All the Fuss)
Trevor Campbell, UBC; Naitong Chen, University of British Columbia; Zuheng Xu, University of British Columbia - Vancouver, BC
12:05 PM Floor Discussion
 
 

137 * !
Mon, 8/8/2022, 10:30 AM - 12:20 PM CC-150A
Joint Modeling for Longitudinal and Survival Outcomes in Health Studies — Topic Contributed Papers
Section on Statistical Computing, WNAR, Biopharmaceutical Section
Organizer(s): Ying Lu, Stanford University School of Medicine
Chair(s): Ellen Snyder, Merck Research Laboratories
10:35 AM Joint Model for Survival and Multivariate Sparse Functional Data with Application to a Study of Alzheimer's Disease
Cai Li, St. Jude Children's Research Hospital; Luo Xiao, North Carolina State University; Sheng Luo, Duke University
10:55 AM Efficient Algorithms and Implementation of a Semiparametric Joint Model for Longitudinal and Competing Risks Data, with Applications to Massive Biobank Data Presentation
Shanpeng Li, UCLA; Gang Li, University of California, Los Angeles; Ning Li , UCLA; Hong Wang, Central South University; Jin Zhou, UCLA; Hua Zhou, UCLA
11:15 AM A Robust Joint Model of Longitudinal Trajectories and Time-to-Event Data at Biobank Scale
Hua Zhou, UCLA; Jin Zhou, UCLA; Gang Li, University of California, Los Angeles
11:35 AM Joint Modeling in Presence of Informative Censoring in Palliative Care Studies
Quran Wu, University of Florida; Michael Daniels, University of Florida; Zhigang Li, University of Florida
11:55 AM Joint modeling of endpoints can be used to answer various research questions in randomized clinical trials
Ruben van Eijk, University Medical Center Utrecht (UMCU), Utrecht, the Netherlands
12:15 PM Floor Discussion
 
 

158
Mon, 8/8/2022, 10:30 AM - 11:15 AM CC-Hall D
SPEED: Statistical Methods, Computing, and Applications Part 2 — Contributed Poster Presentations
International Society for Bayesian Analysis (ISBA), Section on Nonparametric Statistics, Section on Physical and Engineering Sciences, Section on Statistical Computing, Section on Statistics in Defense and National Security, Section on Statistics in Genomics and Genetics
Chair(s): Rui Xie, University of Central Florida
01: The Role of Berkson Paradox in Significance Testing
Miodrag Lovric, Radford University
02: The growclusters Package for R
Randall Powers, Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics; Terrance D Savitsky, U.S. Bureau of Labor Statistics
03: Analysis of Accelerometer Data from NHANES Database Using Fréchet Single Index Model
Aritra Ghosal , University of California, Santa Barbara ; Wendy Meiring , University of California Santa Barbara ; Alexander Petersen, Brigham Young University; Marcos Matabuena , University of Santiago de Compostela
04: Double Sampling for Informative Coarsening: Considerations for Bias Reduction and Efficiency Gain
Alex Levis, Harvard T.H. Chan School of Public Health; Rajarshi Mukherjee, Harvard T.H. Chan School of Public Health; Rui Wang, Harvard T.H. Chan School of Public Health; Sebastien Haneuse, Harvard T.H. Chan School of Public Health
05: Double Machine Learning in a Semiparametric Approach: An Innovative Causal Inference for Observational Studies
Lynda Aouar, University of Northern Colorado
06: A Comparison of Regression Discontinuity Effect Estimation for Small Samples
Daryl Swartzentruber, The Ohio State University; Eloise E Kaizar, The Ohio State University
07: Reliability for Binary and Ordinal Data in Forensics
Hina Arora, University of California Irvine; Naomi Kaplan-Damary, Hebrew University; Hal S. Stern, University of California-Irvine
08: Approaching Supersaturated Screening as a Pilot Experiment
Michael McKibben, NCSU; Jonathan Stallrich, North Carolina State University
09: Bayesian Modeling of Spatial Molecular Profiling Data at the Single-Cell Level
Jie Yang, The University of Texas at Dallas; Sunyoung Shin, University of Texas at Dallas; Qiwei Li, The University of Texas at Dallas
10: W-BETEL: Bayesian Exponentially Tilted Empirical Likelihood with Parametric Restriction via a Modified Wasserstein Metric
Abhisek Chakraborty, Texas A & M University; Anirban Bhattacharya, Texas A&M University; Debdeep Pati, Texas A&M University
11: Interpretable Modeling of Genotype-Phenotype Landscapes with State-of-the-Art Predictive Power
Peter Tonner, National Institute of Standards and Technology; David Ross, National Institute of Standards and Technology; Abe Pressman, National Institute of Standards and Technology
12: Cybersecurity and Infrastructure Security Agency Enterprise Conceptual Data Model
Swami Natarajan, The MITRE Corporation
13: MCMC-CE: A Novel Approach for Accurate Estimation of the Distributions of Large Quadratic Forms of Normal Variables
Bich Na Choi, Medical College of Georgia, Augusta University; Yang Shi, Augusta University
14: Taking PDE Solutions from Low-Fidelity to High-Fidelity Using Bayesian Dynamic Function on Function Regression
Marie Tuft, Sandia National Laboratories; Daniel Ries, Sandia National Labs
15: Bayesian Iterative Conditional Stochastic Search (BICOSS) for GWAS
Jacob Williams, Virginia Polytechnic Institute and State University; Marco Ferreira, Virginia Tech
16: A Statistical Framework for Deepfake Detection
Shannon Gallagher, Software Engineering Institute, Carnegie Mellon University; Catherine Bernaciak, Software Engineering Institute, Carnegie Mellon University; Jeffrey Mellon, Software Engineering Institute, Carnegie Mellon University; Dominic Ross, Software Engineering Institute, Carnegie Mellon University
17: Multi-Omics Integrative Analysis for Incomplete Data Using Weighted P-Value Adjustment Approaches
Wenda Zhang, University of South Carolina
18: Developing Logistic Regression for the High-Dimensional DNA Methylation Data
Mohamed salem Milad, Arkansas State University
19: A Survey of Likelihood Ratio Method Development and Implementation AcrossMultiple Forensic Disciplines
Lulu Chen, University of Central Florida; Larry Tang, University of Central Florida; Jonathon Phillips, National Institute of Standards and Technology
20: Modeling Sparse Data Using MLE with Applications to Microbiome Data
Hani Aldirawi, California State University San Bernardino
 
 

223584
Mon, 8/8/2022, 12:30 PM - 2:00 PM M-LeDroit Park
Sections on Statistical Computing and Statistical Graphics Joint Business Meeting — Other Cmte/Business
Section on Statistical Computing
Chair(s): Jun Yan, University of Connecticut
 
 

Register 170
Mon, 8/8/2022, 12:30 PM - 1:50 PM CC-Ballroom Level South Prefunction
Section on Statistical Computing P.M. Roundtable Discussion (Added Fee) — Roundtables PM Roundtable Discussion
Section on Statistical Computing
ML19: New Trends of Statistical Computing in Modern Data Science
Faming Liang, Purdue University; Jun Liu, Harvard University
 
 

175 * !
Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-151B
Computational Methods for Complex Data Challenges — Invited Papers
Section on Statistical Computing, WNAR, Section on Statistical Graphics, Caucus for Women in Statistics
Organizer(s): Dehan Kong, University of Toronto
Chair(s): Dehan Kong, University of Toronto
2:05 PM Lagrangian Inference for Ranking Problems
Ethan Fang, Duke University; Yue Liu, Harvard University; Junwei Lu, Harvard University
2:35 PM Joint Matrix Decomposition Regression for Supervised Multi-Omics Data Integration
Yue Wang, Arizona State University; Tim Randolph, Fred Hutch Cancer Center; Jing Ma, Fred Hutch Cancer Center; Ali Shojaie, University of Washington
3:05 PM Delphi's COVIDcast Project: Lessons Learned Building Statistical Software in Real Time
Alex Reinhart, Carnegie Mellon University
3:35 PM Floor Discussion
 
 

180 *
Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-152A
Machine Learning and Artificial Intelligence: Uses and Misuses! — Invited Panel
Section for Statistical Programmers and Analysts, Section on Statistical Computing, Biopharmaceutical Section
Organizer(s): Vipin Arora, Eli Lilly and Company
Chair(s): Vipin Arora, Eli Lilly and Company
2:05 PM Machine Learning and Artificial Intelligence: Uses and Misuses!
Panelists: Mark Van Der Laan, UC Berkeley
Jingjing Chen, Takeda Pharmaceuticals
Jaroslaw Harezlak, Indiana University
Melvin Munsaka, AbbVie Inc
3:40 PM Floor Discussion
 
 

184 * !
Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-149AB
New Developments in Graphing Multivariate Data — Invited Panel
Section on Statistical Graphics, Section on Statistical Computing
Organizer(s): Joyce Robbins, Columbia University
Chair(s): Naomi Robbins, NBR
2:05 PM New Developments in Graphing Multivariate Data
Panelists: Jason Cory Brunson, Laboratory for Systems Medicine, University of Florida
Ursula Laa, University of Natural Resources and Life Sciences
Hengrui Luo, Lawrence Berkeley National Laboratory
 
 

204
Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-140A
Statistical Computing by Deep Learning and Penalization — Contributed Papers
Section on Statistical Computing
Chair(s): David Shilane, Columbia University
2:05 PM A Penalized Poisson Likelihood Approach to High-Dimensional Semiparametric Inference of Doubly-Stochastic Point Processes
Si Cheng, University of Washington; Ali Shojaie, University of Washington
2:20 PM Efficient Computation of High-Dimensional Penalized Generalized Linear Mixed Models by Latent Factor Modeling of the Random Effects
Hillary M. Heiling, University of North Carolina Chapel Hill; Naim U. Rashid, University of North Carolina Chapel Hill; Quefeng Li, University of North Carolina Chapel Hill; Joseph G Ibrahim, University of North Carolina
2:35 PM Efficient Large-Scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks
Pratik Nag, King Abdullah University of Science and Technology; Sameh Abdulah, KAUST; Yiping Hong, King Abdullah University of Science and Technology; Marc Genton, KAUST; Ying Sun, KAUST; Ghulam Qadir, Heidelberg Institute of Theoretical Studies
2:50 PM Vulnerabilities of Learning Models Under Malicious Data and Attack Against Deep Neural Networks
Bowei Xi, Purdue University
3:05 PM Virtual Testing Failure Analysis Using Neural Networks and Gaussian Processes
Thomas Muehlenstaedt, ArgoAI; Roman Nagy, Argo AI; Yunxin Gu, Carnegie Mellon University
3:20 PM Sparse Envelope Quantile Model
Hossein Moradi Rekabdarkolaee, South Dakota State University
3:35 PM Features Extraction via Bayesian Analyses Cum Mixture Probabilistic Models by Extensive Computations
Humayun Kiser, Comilla University; Mian Arif Shams Adnan, Bowling Green State University
 
 

223585
Mon, 8/8/2022, 6:30 PM - 8:00 PM M-Mint
Sections on Statistical Computing and Statistical Graphics Mixer — Other Cmte/Business
Section on Statistical Computing
Chair(s): Jun Yan, University of Connecticut
 
 

229 * !
Tue, 8/9/2022, 8:30 AM - 10:20 AM CC-143A
Geostatistical Computing on Modern Parallel Architectures — Topic Contributed Papers
Section on Statistical Computing, Section on Statistical Learning and Data Science, Section on Physical and Engineering Sciences
Organizer(s): Sameh Abdulah, KAUST
Chair(s): Zhuo Qu, King Abdullah University of Science and Technology
8:35 AM Scalable Gaussian-Process Regression and Variable Selection Using Vecchia Approximations Presentation
Jian Cao, Texas A&M University; Matthias Katzfuss, Texas A&M University; Marc Genton, KAUST; Joe Guinness, Cornell University
8:55 AM Parallel Likelihood Function Optimization to Accelerate Air Pollution Prediction on Large-Scale Systems
Mary Lai Salvana, KAUST; Sameh Abdulah, KAUST; Hatem Ltaief, KAUST; Ying Sun, KAUST; Marc Genton, KAUST; David Keyes, King Abdullah University of Science and Technology
9:15 AM A Sandwich Smoother for Spatio-Temporal Functional Data
Joshua French, University of Colorado Denver; Piotr Kokoszka, Colorado State University
9:35 AM Accelerating Geostatistical Modeling with Mixed-Precision and Tile Low-Rank Algorithms on Large-Scale
Qinglei Cao, Innovative Computing Laboratory, University of Tennessee; Sameh Abdulah, KAUST; Rabab Alomairy, KAUST; Yu Pei, Innovative Computing Laboratory, University of Tennessee; Pratik Nag, King Abdullah University of Science and Technology; George Bosilca, Innovative Computing Laboratory, University of Tennessee; Jack Dongarra, Innovative Computing Laboratory, University of Tennessee; Marc Genton, KAUST; David Keyes, King Abdullah University of Science and Technology; Hatem Ltaief, KAUST; Ying Sun, KAUST
9:55 AM Distributed Inference for a Spatial Bayesian Network with Application to Natural Hazard Risk Assessment
Christopher Krapu, Oak Ridge National Laboratory; Nolan Hayes, Oak Ridge National Laboratory; Robert Stewart, Oak Ridge National Laboratory; Amy Rose, Oak Ridge National Laboratory; Alexandre Sorokine, Oak Ridge National Laboratory; Kuldeep Kurte, Oak Ridge National Laboratory
10:15 AM Floor Discussion
 
 

234 !
Tue, 8/9/2022, 8:30 AM - 10:20 AM CC-102A
New Challenges in Statistical Learning and Inference for Complex Data — Topic Contributed Papers
Section for Statistical Programmers and Analysts, Section on Statistical Learning and Data Science, Section on Nonparametric Statistics, Section on Statistical Computing
Organizer(s): Ganggang Xu, University of Miami
Chair(s): Hou-Cheng Yang, U.S. Food and Drug Administration
8:35 AM Nonparametric Comparison of Time Series via Quantile Periodograms
Lei Jin, Texas A&M University - Corpus Christi
8:55 AM Jointly Modeling and Clustering Tensors in High Dimensions
Biao Cai, Yale University; Emma Jingfei Zhang, University of Miami; Will Wei Sun, Purdue University
9:15 AM On Deep Instrumental Variables Estimate
Ruiqi Liu, Texas Tech University; Zuofeng Shang, New Jersey Institute of Technology; Guang Cheng, Purdue University
9:35 AM Calibrating Multi-Dimensional Complex ODE from Noisy Data via Deep Neural Networks
Kexuan Li Li, Worcester Polytechnic Institute; Fangfang Wang, Worcester Polytechnic Institute; Ruiqi Liu, Texas Tech University; Fan Yang, Eli Lilly and Company; Zuofeng Shang, New Jersey Institute of Technology
9:55 AM Model-Assisted Uniformly Honest Inference for Optimal Treatment Regimes in High Dimension
Yunan Wu, University of Taxas at Dallas; Lan Wang, University of Miami; Haoda Fu, Eli Lilly and Company
10:15 AM Floor Discussion
 
 

CE_23C
Tue, 8/9/2022, 8:30 AM - 5:00 PM CC-146A
Julia for Data Science and Statistical Computing — Professional Development Continuing Education Course
ASA, Section on Statistical Computing
Instructor(s): Hua Zhou, UCLA; Josh Day
Julia (http://julialang.org) is a modern open source programming language for technical computing. Its design offers much greater speed and productivity compared to R or Python, as high-performance code does not need to be wrapped in a low level language like C or Fortran. After almost a decade of active development, Julia reached its first major release v1.0 on Aug 8, 2018 and is quickly gaining popularity in the communities of scientific computing and data science. This course comprises two parts. The first part introduces the Julia package ecosystem for data science, including data ingestion and cleaning, visualization, out-of-core processing, model fitting, and general analytics. The second part covers statistical computing using Julia. It begins with a comparison between Julia, R, and Python, and continues with a tutorial on using Julia for numerical linear algebra, numerical optimization, parallel/distributed computing, and GPU computing. Presenter Dr. Hua Zhou from UCLA has extensive experience in teaching statistical computing and Julia in university classrooms and conference venues. Presenter Dr. Josh Day from Julia Computing is a core developer of the JuliaDB and OnlineStats packages.
 
 

252
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-203AB
Novel Methods in Curve Registration for Functional Data — Invited Papers
Biometrics Section, Section on Statistical Learning and Data Science, Section on Statistical Computing
Organizer(s): Julia Wrobel, Colorado School of Public Health
Chair(s): Jeff Goldsmith, Columbia University
10:35 AM Multimodal Bayesian Registration of Noisy Functions Using an Elastic Metric
James Derek Tucker, Sandia National Laboratories; Lyndsay Shand, Sandia National Laboratories; Kamaljit Derek Chowdhary, Sandia National Laboratories
11:00 AM Bayesian Multilevel Curve Registration
Zhenke Wu, University of Michigan, Ann Arbor; Julia Wrobel, Colorado School of Public Health; Jeff Goldsmith, Columbia University
11:25 AM Simultaneous Warping and Clustering of Functional Electrocardiogram
Wei Yang, University of Pennsylvania; Wensheng Guo, University of Pennsylvania
11:50 AM Registration for Incomplete Non-Gaussian Functional Data
Alexander Bauer, LMU Munich, Germany; Fabian Scheipl, LMU Munich, Germany; Helmut Küchenhoff, LMU Munich, Germany; Alice-Agnes Gabriel, LMU Munich, Germany
12:15 PM Floor Discussion
 
 

253
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-202A
Reprise of ASA’s 2021 Statistical Computing and Graphics Award — Invited Papers
Section on Statistical Graphics, Section on Statistical Computing
Organizer(s): Howard Wainer, unaffiliated
Chair(s): Paul F. Velleman, Cornell University
10:35 AM Graphs as Poetry: C.J. Minard, W.E.B. Du Bois, and the Great Migration
Howard Wainer, unaffiliated
11:15 AM Data Visualization Through Time
Catherine Sabina Durso, University of Denver
11:35 AM Wainer's Wabbits and Other Tales
David Thissen, University of North Carolina at Chapel Hill
11:55 AM Wainer's Data and Stories: A Personal Reflection
Richard D De Veaux, Williams College
12:15 PM Floor Discussion
 
 

269 * !
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-144B
Statistical Process Monitoring Methods — Topic Contributed Papers
Quality and Productivity Section, Section on Statistical Computing
Organizer(s): Eric Chicken, Florida State University
Chair(s): Andrés Barrientos
10:35 AM Adaptive Process Monitoring Using Covariate Information
Kai Yang, Medical College of Wisconsin
10:55 AM Transparent Sequential Learning for Statistical Process Control of Serially Correlated Data
Xiulin Xie, University of Florida
11:15 AM Monitoring Parametric, Nonparametric, and Semiparametric Linear Regression Models Using a Multivariate EWMA Bayesian Control Chart
Chelsea Jones, Virginia Commonwealth University; D'Arcy Mays, Virginia Commonwealth University; AbdelSalam AbdelSalam, Qatar University
11:35 AM Multivariate Monitoring via Trees
Eric Chicken, Florida State University; Daniel Timme, Florida State University; Andres F. Barrientos, Florida State University; Debajyoti Sinha, Florida State University
11:55 AM Floor Discussion
 
 

272 *
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-204B
Approaches in Clustering for Analysis of Emerging Data Types — Topic Contributed Papers
Section on Statistical Learning and Data Science, Section on Statistics and Data Science Education, Section on Statistical Computing
Organizer(s): Tanzy Love, University of Rochester
Chair(s): Qiuyi Wu, University of Rochester
10:35 AM Transformation Mixture Modeling for Skewed Data Groups with Heavy Tails and Scatter
Xuwen Zhu, The University of Alabama; Volodymyr Melnykov, The University of Alabama; Yana Melnykov, The University of Alabama
10:55 AM Mixtures of Matrix Variate Contaminated Normal Distributions
Salvatore Daniele Tomarchio, University of Catania; Michael Gallaugher, Baylor University; Antonio Punzo, University of Catania; Paul David McNicholas, McMaster University
11:15 AM On Measuring Soft Agreement in Clustering
Jeffrey Andrews, University of British Columbia Okanagan; Ryan Browne, University of Waterloo; Chelsey Hvingelby, Concordia University
11:35 AM Uncovering Biological Heterogeneity via Clustering to Identify Gene Expression Networks and Patient Similarity Networks
Anjali Silva, University of Toronto
11:55 AM Discussant: Tanzy Love, University of Rochester
12:15 PM Floor Discussion
 
 

282
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-141
Sampling and Ensembling in Statistical Computing — Contributed Papers
Section on Statistical Computing
Chair(s): Donald E.K. Martin, North Carolina State University
10:35 AM Volume Subsampling for Big Data Linear Regression
Ethan Davis, North Carolina State University; Jonathan Stallrich, North Carolina State University
10:50 AM Some Generalized Linear Models to Explore the Effective Medical Derivatives: Biostatistical Analyses to Ensure Better Services for the Hospital Patients in the Post-COVID Era
Mian Arif Shams Adnan, Bowling Green State University; Silvia Irin Sharna, Bowling Green State University
11:05 AM Robust Ensemble Estimation
Mina Mahbub Hossain, Utah State University; Dr. Kevin Moon, Utah State University
11:20 AM A Two-Stage Adaptive Metropolis Algorithm for Bayesian Calibration of Complex Computer Models
Anirban Mondal, Case Western Reserve University
11:35 AM A Non-Degrading Streaming Sampler for Recursive Bayesian Inference
Ian Taylor, Colorado State University; Andee Kaplan, Colorado State University; Brenda Betancourt, University of Florida
11:50 AM A Unified Framework for Principal Subspace Analysis on Manifolds from the Hamiltonian Viewpoint
Ke Yu, University of Oxford
12:05 PM Floor Discussion
 
 

307 * !
Tue, 8/9/2022, 2:00 PM - 3:50 PM CC-102A
Deep Learning, Nonparametric Statistics, and Beyond — Invited Papers
Section on Nonparametric Statistics, Section on Statistical Learning and Data Science, Section on Statistical Computing, Caucus for Women in Statistics
Organizer(s): Yufeng Liu, University of North Carolina
Chair(s): Yufeng Liu, University of North Carolina
2:05 PM Kernel Estimation of Bivariate Time-Varying Coefficient Model for Longitudinal Data with Terminal Event
Bin Nan, University of California, Irvine; Yue Wang, University of California, Irvine; Jack Kalbfleisch, University of Michigan
2:30 PM Optimal Omni-Channel Individualized Treatment Rules Under Budget Constraints Using Deep Learning
Qi Xu, Unviersity of California Irvine; Haoda Fu, Eli Lilly and Company; Annie Qu, UC Irvine
2:55 PM Sleep Classification with Artificial Synthetic Imaging Data Using Convolutional Neural Networks
Peter Song, University of Michigan; Lan Shi, University of Michigan ; Marianthie Wank, University of Michigan; Yan Chen, University of Michigan ; Yibo Wang, University of Michigan; Emily Charlotte Hector, North Carolina State University
3:20 PM Population-Level Balance in Signed Networks
Weijing Tang, University of Michigan; Ji Zhu, University of Michigan
3:45 PM Floor Discussion
 
 

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
 
 

347
Tue, 8/9/2022, 2:00 PM - 3:50 PM CC-Hall D
Contributed Poster Presentations: Section on Statistical Computing — Contributed Poster Presentations
Section on Statistical Computing
Chair(s): Gyuhyeong Goh, Kansas State University
36: Subsampling Based Community Detection in Large Networks
Sayan Chakrabarty, University of Illinois at Urbana Champaign; Srijan Sengupta, NCSU; Yuguo Chen, University of Illinois at Urbana-Champaign
37: Robustifying and Increasing Performance of Models for a Categorical Response Using Improved Variable Selection
Myriam Maumy, Troyes Technology University; Frédéric Bertrand, Troyes Technology University
 
 

368 * !
Wed, 8/10/2022, 8:30 AM - 10:20 AM CC-150A
Recent Advances in Statistical Network Analysis with Applications — Invited Papers
Section on Statistical Graphics, Section on Statistical Learning and Data Science, Section on Statistical Computing
Organizer(s): Ji Zhu, University of Michigan
Chair(s): Ji Zhu, University of Michigan
8:35 AM Nonparametric Inference Under a Birth-Death Dynamic Network Model
Soumendra Lahiri, Washington University in St Louis
9:00 AM Identifying the Latent Space Geometry of Network Models Through Analysis of Curvature
Shane Lubold, University of Washington; Arun Chandrasekhar, Stanford University; Tyler McCormick, University of Washington
9:25 AM Using Maximum Entry-Wise Deviation to Test the Goodness of Fit for Stochastic Block Models
Emma Jingfei Zhang, University of Miami
9:50 AM Informative Core Identification in Complex Networks
Ruizhong Miao, University of Virginia; Tianxi Li, University of Virginia
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
 
 

426 * !
Wed, 8/10/2022, 10:30 AM - 12:20 PM CC-144B
Computing in Large and Complex Data Analysis — Contributed Papers
Section on Statistical Computing
Chair(s): Ian Taylor, Colorado State University
10:35 AM Graph Topology Learning from Smooth Signal on the Graph and Predictors
Jing Guo, California State University, Chico; Skip Moses, California State University, Chico
10:50 AM WITHDRAWN High Order Candecomp/Parafac Model for Complex Data
Michele Gallo, University of Naples - L'Orientale
11:05 AM Generalized Kernel Thinning
Raaz Dwivedi, MIT
11:20 AM A Benchmarking Suite for Geostatistical Modeling and Kriging Tools
Faten Alamri , Princess Nourah Bint AbdulRahman University &KAUST ; Sameh Abdulah, KAUST; Marc Genton, KAUST; David Keyes, King Abdullah University of Science and Technology; Hatem Ltaief, KAUST; Ying Sun, KAUST
11:35 AM Parallel Approximation of the Tukey G-and-H Likelihoods for Large-Scale Non-Gaussian Geostatistical Modeling
Sagnik Mondal, King Abdullah University of Science and Technology; Sameh Abdulah, KAUST; Hatem Ltaief, KAUST; Ying Sun, KAUST; Marc Genton, KAUST; David Keyes, King Abdullah University of Science and Technology
12:05 PM Floor Discussion
 
 

455 * !
Wed, 8/10/2022, 2:00 PM - 3:50 PM CC-151A
Learning Under Nonstationarity — Invited Papers
Section on Statistical Learning and Data Science, Section on Nonparametric Statistics, Section on Statistical Computing
Organizer(s): Piotr Fryzlewicz, London School of Economics
Chair(s): David Matteson, Cornell University
2:05 PM Nonstationary Reinforcement Learning Without Prior Knowledge: An Optimal Black-Box Approach Presentation
Chen-Yu Wei, University of Southern California; Haipeng Luo, University of Southern California
2:25 PM Testing Nonstationary and Policy Optimization in Reinforcement Learning
Chengchun Shi, London School of Economics and Political Science; Mengbing Li, University of Michigan; Zhenke Wu, University of Michigan, Ann Arbor; Piotr Fryzlewicz, London School of Economics
2:45 PM A Similarity Measure for Second-Order Properties of Nonstationary Functional Time Series with Applications to Clustering and Testing
Anne van Delft, Columbia University; Holger Dette, Ruhr University Bochum
3:05 PM Bandit Learning with Endogenous Drift
assaf zeevi, columbia university
3:25 PM Discussant: Piotr Fryzlewicz, London School of Economics
3:45 PM Floor Discussion
 
 

479 *
Wed, 8/10/2022, 2:00 PM - 3:50 PM CC-152B
What We Learned Statistically Through COVID-19 Pandemic-Related Research — Topic Contributed Panel
Section on Statistical Computing, Section on Statistics in Epidemiology, Biometrics Section
Organizer(s): Usha Govindarajulu, Icahn School of Medicine at Mount Sinai
Chair(s): Hung-Mo Lin, Icahn School of Medicine at Mount Sinai
2:05 PM What We Learned Statistically Through COVID-19 Pandemic-Related Research
Panelists: Bhramar Mukherjee, University of Michigan
Dean Follmann, National Institute of Allergy and Infectious Diseases
Alex Luedtke, University of Washington
Jeffrey Morris, University of Pennsylvania
Usha Govindarajulu, Icahn School of Medicine at Mount Sinai
3:40 PM Floor Discussion
 
 

494 * !
Thu, 8/11/2022, 8:30 AM - 10:20 AM CC-151A
Advanced Developments in Methods and Algorithms for Modern Complex Imaging Data — Invited Papers
Section on Statistical Computing, Section on Statistics in Imaging, ENAR, Biometrics Section
Organizer(s): Lily Wang, George Mason University; Shan Yu, University of Virginia
Chair(s): Xinyi Li, Clemson University
8:35 AM Mixture of Multivariate Sparse Regressions Modeling for Oceanographic Flow Cytometry Data
Jacob Bien, University of Southern California; Sangwon Hyun, University of Southern California; François Ribalet, University of Washington; Mattias Cape, University of Washington
9:00 AM Generalized Liquid Association Analysis for Multimodal Data Integration
Lexin Li, University of California, Berkeley; Jing Zeng, Florida State University; Xin Zhang, Florida State University
9:25 AM Spline Smoothing of 3-D Geometric Data
Shan Yu, University of Virginia; Xinyi Li, Clemson University; Yueying Wang, Columbia University; Guannan Wang, College of William and Mary; Lily Wang, George Mason University
9:50 AM Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging
Andrew Brown, Clemson University; Christopher McMahan, Clemson University; Russell Shinohara, University of Pennsylvania; Kristin Linn, University of Pennsylvania
10:15 AM Floor Discussion
 
 

501
Thu, 8/11/2022, 8:30 AM - 10:20 AM CC-143B
Bayesian Penalized Likelihood Methods for Gaussian Graphical Models — Invited Papers
Section on Bayesian Statistical Science, Section on Nonparametric Statistics, Section on Statistical Computing
Organizer(s): Abhra Sarkar, The University of Texas at Austin
Chair(s): Veronica J Berrocal, University of California
8:35 AM New Directions in Bayesian Shrinkage for Structure Learning
Ksheera Sagar K. N. , Purdue University; Sayantan Banerjee, Indian Institute of Management Indore; Jyotishka Datta, Virginia Tech; Anindya Bhadra, Purdue University
9:05 AM Bayesian Scalable Precision Factor Analysis for Massive Sparse Gaussian Graphical Models
Noirrit Kiran Chandra, The University of Texas at Austin; Abhra Sarkar, The University of Texas at Austin; Peter Mueller, The University of Texas at Austin
9:35 AM Quantile Graphical Models: A Bayesian Approach
Nilabja Guha, University of Massachusetts Lowell; Veera Baladandayuthapani, University of Michigan; Bani Mallick, Texas A&M University
10:05 PM Floor Discussion
 
 

551
Thu, 8/11/2022, 10:30 AM - 12:20 PM CC-143A
Statistical Machine Learning and Artificial Intelligence in Multi-Parametric Quantitative Imaging — Topic Contributed Papers
Section on Statistical Computing, Section on Statistics in Imaging
Organizer(s): Xiaofeng Wang, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University
Chair(s): Gene Anthony Pennello, Food and Drug Administration
10:35 AM STATISTICAL THINKING, SYSTEMATIC REVIEWS, AND META-ANALYSES FOR BIOMAKERS AND MEDICAL TESTS Presentation
Arkendra De, Agilent Technologies
10:55 AM Phenotype Classification with Multiparametric Quantitative Imaging Biomarkers
Jana Delfino, US Food and Drug Administration, CDRH
11:15 AM Issues in the Development and Validation of Quantitative Imaging Biomarker-Based Models
Erich Huang, National Cancer Institute
11:35 AM Machine Learning in Radiomics: A Practical Guide for Modeling with Data-Driven Imaging Markers
Xiaofeng Wang, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University
11:55 AM Discussant: Weijie Chen, U.S. Food and Drug Administration (FDA)
12:15 PM Floor Discussion