Submitted Abstracts
Abstracts:
Mithun Acharjee - Statistical Shape Analysis of 3DFN Data: Analysis via Deformetrica
Aaid Algahtani - Limit Theorems for Object Data with Applications to 3D Image Data Analysis
Badr Aloraini - Estimation of Population Variance for a Sensitive Variable in Stratified Sampling Using Randomized Response Technique
Katie Anderson - A New Benford Test for Clustered Data with Applications to American Elections
Forgive Avorgbedor - Effects of Neighborhood and Household Socioeconomic Disadvantage on Postpartum Weight Retention
Sarangan Balasubramaniam - Spatial Prediction for Axially Symmetric Process on Spheres
David Banks - Route Choice Under Uncertainty: An Adversarial Risk Analysis
Mahabir Barak - Reliability Measures Evaluation of a Cold Standby System using Refreshment Facility under Environment Conditions
Frances Buderman - A Life-History Spectrum of Population Responses to Simultaneous Change in Climate and Land Use
Guanqun Cao - Deep Neural Network Classifier for Functional Data
Elvan Ceyhan - Comparison of Various Algorithms in Optimal Obsta Placement with Disambiguation (OPD) Problem
Seunghee Choi - Estimation of Spherical Depth on Object Spaces
Joy D’Andrea - A Brief Parametric Analysis of Catastrophic or Disastrous Hurricanes That Have Hit the Florida Keys between 1900 and 2000
Kumer Das - Air Quality and Lung Cancer: Analysis via Local Control
Richard Davis - Time Series Estimation of the Dynamic Effects of Disaster-Type Shocks
Xinwei Deng - A Machine Learning Perspective for Experimental Design via Tight Mutual Information
Adam Dixon - Investigating Two Possible Origins of SARS-CoV-2: An RNA Analysis on Tree Spaces
Alexander Dombowsky - Bayesian Multi-Study Clustering of Sepsis Patients: Utilizing Prior Information and Testing Cluster Discovery
Ian Dryden - Shape Analysis of Molecular Dynamics Data
David Edwards - Strategies for Supersaturated Screening: Group Orthogonal and Constrained Var(s) Designs
Ciaran Evans - Two-Sample Testing With Local Community Depth
Crystal Modde Epstein and Thomas P. McCoy - Mixed-Effects Cosinor Analysis of Cortisol Patterns Among Pregnant Women
Marco Ferreira - Bayesian Analysis of GLMMs with Nonlocal Priors for Genome-Wide Association Studies
John Foley - Learning Communities in Data From Probabilistic Estimates of Similarity
Robert Gramacy - Deep Gaussian Process Surrogates for Computer Experiments
Shaymal Halder - The Interplay of Biomass Energy Consumption on Ecological Footprint: Using Parametric and Time-Varying Non-parametric Approaches
Daniel Hall - Statistical Consulting in a University Setting: Modern Challenges and Enduring Issues
Bill Heavlin - Active Learning Meets Experimental Design Theory
Emily Hector - Mean Structure Learning with High-Dimensional Correlated Data
Yiren Hou - Optimal Design for Ordinal Categorical Regression on Milk Fiber Strength
Jenny Huang - Online Controlled Experiments: Top Challenges and Solutions
Marianne Huebner - Quantile Foliation - Smoothing to Model Performance in Olympic Weightlifting Across the Life Span
Mohammad Saiful Islam - Impact of Establishment of Liquid Medical Oxygen System Indifferent Health Facility to Provide Quality Care of Critical Patient During Covid-19 Crisis in Bangladesh
Eiren Jacobson - Quantifying the Response of Blainville’s Beakedwhales to U.S. Naval Sonar Exercises in Hawaii
Eiren Jacobson - State-Space Models for Marine Mammal Populations
Matt Jester - Robust Topological Classification with Applications in Firn Data Analysis
Jiancheng Jiang - Testing for Irrelevance in Partially Parametric Models With Parametric Nulls
Zhezhen Jin - A Step-Wise Multiple Testing With Linear Regression Models for the Study of Resting Energy Expenditure
Karen Kafadar - To Screen or Not to Screen? Using Data From Randomized Screening Trials to Quantify Risks & Benefits of Cancer Screening
Lulu Kang - Dimension Reduction for Gaussian Process Models via Convex Combination of Kernels
Jakini Kauba - An Analysis of Demographic Trends Using Topological Data Analysis
Timothy Keaton - Actively Learning About Active Learning
Sadia Khalil - Mean Estimation Using RRT Models Under Two-Phase Simple & Stratified Random Sampling Designs
Zekican Kazan - Statistical Disclosure Risk with Differential Privacy, with Application to the 2020 Decennial Census
Zaheen Khan - Application of Modified Systematic Sampling in Auto-correlated Populations
Zaheen Khan - Unbiased Estimation of Variance of Sample Mean in Systematic Sampling
Woojin Kim - Computing Generalized Rank Invariant via Zigzag Persistence
Younghoon Kim - Latent Gaussian Dynamic Factor Modeling and Forecasting for Multivariate Count Time Series
Sheela Kumari - Development of the Subject Statistics: A Historical Perspective
Soumendra Lahiri - A Scalable Method for Fitting Sparse Markov Models
Patrick LeBlanc - Cross-Domain Recommender Systems
Ryan Lekivetz - A Family of Orthogonal Main Effects Screening Designs for Mixed Level Factors
Anthony Lee - Generalizing the German Tank Problem
Ben Seiyon Lee - A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets
Didong Li - Probabilistic Contrastive Principal Component Analysis
Kevin Li - Variational Manifold-Embedded Gaussian Process Modeling, With Applications to Aircraft Engine Design
Mingyan Li - Probabilistic Factorization Matrix
Quefeng Li - Decomposition of Variation of Mixed Variables by a Latent Mixed Gaussian Copula Model
Xinyi Li - Individualized Treatment Regimes Incorporating Imaging Features
Yao Li - Trusted Aggregation (TAG): Model Filtering Backdoor Defense In Federated Learning
Xiaoyan “Iris” Lin - Bayesian Gaussian Copula Graphical Model for Ordinal Data
Regina Liu - Fusion Learning: Combine Inferences From Diverse Data Sources
Tuhin Majumder - Fitting Sparse Markov Models Through Regularization
Suresh Chander Malik - On Use of Regression Approach for Reliability Variation of a Parallel-Series System
Abhyuday Mandal - Modeling and Active Learning for Experiments with Quantitative-Sequence Factors
Marianthi Markatou - Smoothing Kernels for Categorical and Mixed-Scale Data
Vasileios Maroulas - Random Persistence Diagram Generator
Donald E.K. Martin - Inference for Hidden Sparse Markov Models
Wendy Martinez - What’s the Big Deal With Data Ethics, and Why Should I Care?
Sunil Mathur - Cancer Data Science: Drug Testing in Cancer Research Using Auxiliary Information
William McCance - Binary Randomized Response Technique (RRT) Models Under Measurement Error
Thomas P. McCoy and Marjorie Jenkins - Time-to-ICU Transfer by Frailty Severity using Electronic Health Record Data: Does Nursing Flowsheet Data Matter?
Zoe McDonald and Livia Betti - Benfordness of Measurements Resulting From Box Fragmentation
Bailey Meche - DiseaseNet: a Unified Approach to Disease Detection
April W. Messer - Nurses’ Experiences Caring for Patients with Opioid Use Disorders
Abu Minhajuddin - Identifying Subgroups of Adolescents With Depression Suicidal Ideation: A Look at the TX-YDSRN Data
John Morgan - A New Look at the Search Design Concept
Shah Golam Nabi - Initiatives of Emergency Response and COVID-19 Pandemic Preparedness for Health System Strengthening to Combat COVID -19 Pandemic in Bangladesh
Tom Needham - Hypergraph Co-Optimal Transport
Leslie New - Balancing Wind Energy Production and Bat Fatalities
Wei Ning - Monitoring Sequential Structural Changes in Penalized High-Dimensional Linear Models
Rhys O’Higgins - Subdata Selection and TreeS
Vic Patrangenaru - RCD and TDA for 2D Scenes Extracted From Electronic Images
Antony Pearson - Hidden Independent Models in Hole-y Unstructured Sources
Rick Presman - Inference for Distance-to-Set Regularization via Constrained Bayesian Inference
Neil Pritchard - Coarse Embeddability of the Space of Persistence Diagrams and Wasserstein Space
Wanli Qiao - Embedding Functional Data: Multidimensional Scaling and Manifold Learning
Jerry Reiter - How Auxiliary Information Can Help Your Missing Data Problem
Grace Rhodes - Markov Chain Composite Likelihood and Its Application in Genetic Recombination Model
Anuradha Roy - Linear Models for Doubly Multivariate data with Exchangeably Distributed Errors
Fatema Ruhi - A Comparison of Multiple Testing Procedures for Controlling the False Discovery Rate Under Unequal Variances
Arman Sabbaghi - A Bayesian Analysis of Two-Stage Randomized Experiments in the Presence of Interference, Treatment Nonadherence, and Missing Outcomes
Pujita Sapra - Accounting for Lack of Trust in Optional Binary RRT Models Using a Unified Measure of Privacy and Efficiency
Annie Sauer - Active Learning for Deep Gaussian Process Surrogates
Radmila Sazdanovic - Mapper-Type Algorithms: Extensions and Generalizations
MD Shahjahan - Predictors of Depression and Anxiety Among Urban Population During COVID-19: An Online Cross-Sectional Survey
Qin Shao - Simultaneous Confidence Band Approach for Comparison of COVID-19 Case Counts
Don Sheehy - Semi-Supervised TDA
Flora Shi - ESPs: A New Cost-Efficient Sampler for Expensive Posterior Distributions
Chenlu Shi - A Projection Space-Filling Criterion and Related Optimality Results
Wenhao Shou - Kernel Density Estimation Using Additive Randomized Response Technique (RRT) Models
Sean Simpson - Analytical Tools for Whole-Brain Networks: Fusing Statistics and Network Science to Understand Brain Function
Rakhi Singh - Design Selection for Supersaturated Designs
John Stufken - Subdata Selection With a Large Number of Variables
Jianping Sun - Repeated Sampling in EMA Studies: A Discussion Statistical Challenge and Potential Solution
Chih-Li Sung - Functional-Input Gaussian Processes with Applications to Inverse Scattering Problems
Emily Tallman - Bayesian Predictive Decision Synthesis: Betting on Better Models
Ryan Tang - Ad Marketplace Optimization Towards Auto-Bidding
Ye Tian - Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Srinivasa Varadhan - The Polaron Problem
Cuiling Wang - Optimal Cut-Point for Disease Incidence With Censored Data
Guannan Wang - Statistical Inference for Mean Functions of 3D Functional Objects
HaiYing Wang - Maximum Sampled Conditional Likelihood for Informative Subsampling
Jing Wang - Semiparametric Estimation of Non-Ingroable Missingness with Refreshment Sample
Lin Wang - Balanced Subsampling for Big Data with Categorical Predictors
Rui Wang - Assessing Exposure-Time Treatment Effect Heterogeneity in Stepped Wedge Cluster Randomized Trials
Yuan Wang - Topological Inference on Brain Signals
Md Shamim Sarker - Bayesian Pooled Testing Regression With Measurement Error
Sophia Waymyers - Modeling Negatively Skewed Survival Data in Accelerated Failure Time Models
Justin Weltz - Hidden Population Estimation With Auxiliary Information
Haolei Weng - Signal-To-Noise Ratio Aware Minimaxity for Sparse Gaussian Sequence Models
Qian Xiao - Maximum One-Factor-At-A-Time Designs for Screening in Computer Experiments
Xiaohuan Xue - Constructing Covariance Functions for Axially Symmetric Processes on the Sphere
Min Yang - Selecting Nearly Optimal Subdata
Yuyan Yi - CW_ICA: An Efficient Dimensionality Selection Method for Independent Component Analysis
Yubai Yuan - Query-Augmented Active Metric Learning
Hongbin Zhang - Statistical Methods for Interval-Censored Multistate Data and Mis-Measured Covariates With Application in HIV Care
Joia Zhang - An Optional Quantitative Mixture RRT Model that Accounts for Lack of Trust
Zhengwu Zhang - High-Dimensional Spatial Quantile Function-on-Scalar Regression
Xiaojun Zheng - PERCEPT: a New Online Change-Point Detection Method Using Topological Data Analysis
Paul Zivich - Targeted Maximum Likelihood Estimation With Network-Dependent Data