Conference Program

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Key:

Computational Statistics
Computational Statistics
Data Visualization
Data Visualization
Education
Education
 
Machine Learning
Machine Learning
Practice and Applications
Practice and Applications
Software & Data Science Technologies
Software & Data Science Technologies
Thursday, June 9
Registration
SDSS Hours
Thu, Jun 9, 8:00 AM - 5:15 PM
Allegheny Grand Ballroom Foyer
 

SDSS Expo
SDSS Hours
Thu, Jun 9, 8:00 AM - 4:00 PM
Allegheny Grand Ballroom Foyer
 

Speed Mentoring (pre-registration required)
Social Event
Thu, Jun 9, 8:00 AM - 8:45 AM
Allegheny I
 

Are you looking for a quick way to make connections, solicit career advice, and develop professional relationships? Or maybe you want to provide advice and guidance to early-career statisticians and data scientists? Whether you are interested in mentoring or being mentored, you should consider participating in our speed mentoring session. This is a great opportunity for both mentors and mentees to build their professional networks!

Registration Forms: https://ww2.amstat.org/meetings/sdss/2022/events.cfm

GS02 - Plenary: Career Panel
General Session
Thu, Jun 9, 8:45 AM - 9:45 AM
Allegheny Grand Ballroom
 
Chair(s): Alicia Lamere, Bryant University

LB - Statistical Approaches for Privacy-Preserving Methodologies
Late Breaking
Thu, Jun 9, 10:30 AM - 12:00 PM
Allegheny Grand Ballroom
 
Chair(s): Claire Bowen, Urban Institute

10:35 AM
A Formal Privacy Framework for Partially Private Data
Jeremy Seeman, Penn State University
11:00 AM
Developing a Feasible Differentially Private Validation Server for Administrative Tax Data
Joshua Snoke, RAND Corporation
11:25 AM
Differential Privacy on Manifolds
Carlos Soto, Penn State University
Practice and Applications
CS11 - Data Science in Clinical Contexts
Refereed
Thu, Jun 9, 10:30 AM - 12:00 PM
Butler
 
Chair(s): Ryan Peterson, Colorado School of Public Health

10:35 AM
When to Initiate Cancer Screening Exam if Sensitivity Is a Function of Sojourn Time?
Presentation Dongfeng Wu, University of Louisville
11:00 AM
Active Data Science for Improving Clinical Risk Prediction
Donna Pauler Ankerst, Technical University of Munich
11:25 AM
Investigating Racial Disparities in Assisted Reproductive Technology Utilization and Outcomes: A Case Report on a Complex Missing Data Problem
Katharine Correia, Amherst College
Computational Statistics
CS12 - High-dimensional Statistics
Refereed
Thu, Jun 9, 10:30 AM - 12:00 PM
Cambria
 
Chair(s): Xiaoqian Liu, North Carolina State University

10:35 AM
Comparing Methods for Statistical Inference with Model Uncertainty
Anupreet Porwal, University of Washington
11:00 AM
UniCATE: Flexible Predictive Biomarker Discovery
Presentation Philippe Boileau, Graduate Group in Biostatistics and Center for Computational Biology, UC Berkeley; Roche Canada
11:25 AM
Generalizable Manifold Learning for Dimensional Reduction
Jungeum Kim, Purdue University
Machine Learning
CS13 - Data Mining and Deep Learning
Refereed
Thu, Jun 9, 10:30 AM - 12:00 PM
Fayette
 
Chair(s): Mingzhao Hu, University of California, Santa Barbara

10:35 AM
Model-Agnostic AI Assurance Scoring Framework
Md Nazmul Kabir Sikder, Virginia Tech
11:00 AM
Malfunction Analysis in Processes Based on Rule Mining
Benoit Vuillemin, IRMA - UMR 7501 - CNRS
11:25 AM
Random Forest to Estimate a Dose-Response Relationship in Quasi-Experimental Student Success Studies
Richard A Levine, San Diego State University
Practice and Applications
CS14 - Applying and Evaluating Logistic Regression Models
Refereed
Thu, Jun 9, 1:15 PM - 2:45 PM
Allegheny Grand Ballroom
 
Chair(s): Seema Sangari, Kennesaw State University

1:20 PM
Searching the Web for the Drone Industry: Classifying Websites in Multiple Countries and Languages with a Single Model
Presentation Piet J.H. Daas, Statistics Netherlands
1:45 PM
Residuals and Diagnostics for Multinomial Regression Models
Eric Anthony El-Khouri Gerber, California State University, Bakersfield
Data Visualization
CS15 - Assessing and Evaluating Data with Visualizations
Refereed
Thu, Jun 9, 1:15 PM - 2:45 PM
Butler
 
Chair(s): Maya Shen, Carnegie Mellon University

1:20 PM
‘You Draw It’: Implementation of Visually Fitted Trends with R2d3
Presentation Emily A. Robinson, University of Nebraska - Lincoln
1:45 PM
Model Diagnostics of Discrete Data Regression: A Unifying Framework Using Functional Residuals
Presentation Zewei Lin, University of Cincinnati
2:10 PM
Designing COVIDcast 2.0, Implementing Emergent Data Visualization Designs from the COVID-19 Pandemic
Chris Scott, Google, Inc.
Machine Learning
CS16 - Advancements in Machine Learning
Refereed
Thu, Jun 9, 1:15 PM - 2:45 PM
Cambria
 
Chair(s): Qiyu Wang, Zhejiang University of Finance and Economics

1:20 PM
Combining Capsule Networks and Self-Supervised Learning for Image Classification with Occlusion
Ladyna Wittscher, Friedrich-Schiller-University Jena, Germany
1:45 PM
A Convex-Nonconvex Strategy for Grouped Variable Selection
Presentation Xiaoqian Liu, North Carolina State University
2:10 PM
Recalibrating Probability Density Estimates Using Feature-Space Regression
Biprateep Dey, University of Pittsburgh
Practice and Applications
Machine Learning
CS17 - Data-driven Healthcare
Lightning
Thu, Jun 9, 1:15 PM - 2:45 PM
Fayette
 
Chair(s): Xiaoqing "Ellen" Tan, University of Pittsburgh

1:20 PM
R-Based Clinical Trial Submission to FDA
Presentation Ning Leng, Genentech, Inc.
1:25 PM
A Predictive Model for Speech Rehabilitation for Patients with Parkinson’s Disease
Ismail EL Moudden, Eastern Virginia Medical School Sentara Healthcare Analytics and Delivery Science Institute
1:30 PM
fiBAG: Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Genomic Data
Presentation Rupam Bhattacharyya, University of Michigan
1:35 PM
Defining New Staging Criteria for Metastatic Breast Cancer Using Recursive Partitioning
Presentation Samantha M. Thomas, Duke University
1:40 PM
CAMO: A molecular congruence analysis framework for evaluating model organisms
Wei Zong, Department of Biostatistics, University of Pittsburgh
1:45 PM
Comparing Methods for Evaluating the Proportional Hazards Assumption for Time-to-Event Survey Data
John R Pleis, National Center for Health Statistics
1:50 PM
Variable selection in the development of ICU scoring systems
Presentation Gary David Sharp, Nelson Mandela University
1:55 PM
Modeling COVID-19 disruptions in longitudinal health registry data: a case study of conventional methods producing incoherent results
Presentation Raymond Pomponio, Colorado School of Public Health
2:00 PM
Neural-Network Models for Long-term Care Insurance Insolvency: An Enterprise Risk Management Approach
Sebastain Awondo, University of Alabama
2:05 PM
CircadianPipeline: A pipeline for differential rhythmicity analysis in R/Shiny
Xiangning Xue, University of Pittsburgh
2:10 PM
Delayed Phase Scan Prediction for Multiphase Liver CT Dose Reduction
Presentation Bin Chen, Purdue University Fort Wayne
Practice and Applications
Machine Learning
PS03 - Data-driven Healthcare, Part 2
Lightning Poster
Thu, Jun 9, 2:45 PM - 3:40 PM
Allegheny I
 

1
R-Based Clinical Trial Submission to FDA
Ning Leng, Genentech, Inc.
2
A Predictive Model for Speech Rehabilitation for Patients with Parkinson’s Disease
Ismail EL Moudden, Eastern Virginia Medical School Sentara Healthcare Analytics and Delivery Science Institute
3
fiBAG: Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Genomic Data
Rupam Bhattacharyya, University of Michigan
4
Defining New Staging Criteria for Metastatic Breast Cancer Using Recursive Partitioning
Samantha M. Thomas, Duke University
5
CAMO: A molecular congruence analysis framework for evaluating model organisms
Wei Zong, Department of Biostatistics, University of Pittsburgh
6
Comparing Methods for Evaluating the Proportional Hazards Assumption for Time-to-Event Survey Data
John R Pleis, National Center for Health Statistics
7
Variable selection in the development of ICU scoring systems
Gary David Sharp, Nelson Mandela University
8
Modeling COVID-19 disruptions in longitudinal health registry data: a case study of conventional methods producing incoherent results
Raymond Pomponio, Colorado School of Public Health
9
Delayed Phase Scan Prediction for Multiphase Liver CT Dose Reduction
Bin Chen, Purdue University Fort Wayne
10
Neural-Network Models for Long-term Care Insurance Insolvency: An Enterprise Risk Management Approach
Sebastain Awondo, University of Alabama
11
CircadianPipeline: A pipeline for differential rhythmicity analysis in R/Shiny
Xiangning Xue, University of Pittsburgh
Practice and Applications
CS18 - Improving Algorithms for Big Data
Refereed
Thu, Jun 9, 3:45 PM - 5:15 PM
Allegheny Grand Ballroom
 
Chair(s): Yu "Wayne" Wang, University of Michigan

3:50 PM
Building the Foundation for More Flexible A/B Testing: Applications of Interim Monitoring to Large-Scale Data
Presentation Wenru Zhou, University of Colorado
4:15 PM
Time Series Anomaly Detection in the Age of Big Data: Matching Data Generation Processes with Algorithms
Gorkem Turgut Ozer, University of New Hampshire
Software & Data Science Technologies
CS19 - Contributions to Software and Technology
Refereed
Thu, Jun 9, 3:45 PM - 5:15 PM
Butler
 
Chair(s): Emily Dodwell, AT&T

3:50 PM
Csurvey: Implementing Order Constraints in Survey Data Analysis
Xiyue Liao, California State University, Long Beach
4:15 PM
WITHDRAWN Practical Target-Based Synchronization Strategies for Immutable Time-Series Data Tables
Machine Learning
CS20 - Neural Network Analysis
Refereed
Thu, Jun 9, 3:45 PM - 5:15 PM
Cambria
 
Chair(s): Ilia Sucholutsky, University of Waterloo

3:50 PM
Predicting Crop-Specific Land Cover Using Transition Probabilities, Deep and Quantum-Inspired Neural Network Models
Luca Sartore, National Institute of Statistical Sciences
4:15 PM
Comprehensive Evaluation of CNNs for Pollen Classification
Presentation Predrag Matavulj, BioSense Institute
4:40 PM
A Novel Architecture Combining Central-Peripheral Deviation with Convolutional Neural Networks for Diffusion Tensor Imaging Studies
Presentation Soyun Park, University at Buffalo
Computational Statistics
Machine Learning
CS21 - New Models, Methods, and Applications I
Lightning
Thu, Jun 9, 3:45 PM - 5:15 PM
Fayette
 
Chair(s): Francis Bilson Darku, University of Notre Dame

3:50 PM
CGMM: an algorithm for constrained model-based clustering
Jian Zou, Department of Biostatistics, School of Public Health, University of Pittsburgh
3:55 PM
A Semiparametric Modeling Approach for Analyzing Clinical Biomarkers Restricted to Limits of Detection
Sandipan Dutta, Old Dominion University
4:00 PM
Bayesian Poisson Model with Spatio-temporal Structure for Mortality Projection of Multi-population
Zhen Liu, Department of Mathematics & Statistics, Georgetown University
4:05 PM
Empirically adjusted weighted ordered p-values method for meta-analysis
Sinjini Sikdar, Old Dominion University
4:10 PM
Confidence Intervals for Genetic Correlation via Parametric Bootstrap
Yi-Ting Tsai, Harvard T.H. Chan School of Public Health
4:15 PM
A California Wetland Case Study: A Novel, Predictive Approach to Monitor Estuarine Health
Vedant Janapaty, Silver Creek High School
4:20 PM
Use of Process Crowding in Conditional WGAN for Remaining Process Events Prediction
Presentation Yoann Valero, LIST3N, Université de Technologie de Troyes
4:25 PM
Variable Importance Confidence Intervals within Random Forest
Presentation Heather Lynn Cook, University of Southern Indiana
4:30 PM
A New, Global Estimate of Biocrust Carbon and Nitrogen Flux from Terrestrial Ecosystems
Shloka V. Janapaty, Columbia University

 

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