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Key:
Computational Statistics
Data Visualization
Education
Machine Learning
Practice and Applications
Software & Data Science Technologies
Wednesday, June 8
CS01 -
Using Statistics to Prepare for the Future
Refereed
Wed, Jun 8, 10:30 AM - 12:00 PM
Allegheny Grand Ballroom
Chair(s): Emily Griffith, Data Science Academy, NC State
10:35 AM
Storm-Based Estimation of Design Snow Load on Solar Panels
Presentation
Kenneth Kin Pomeyie, Utah State University
11:00 AM
Forecasting Weekly Natural Gas Consumption in Residential and Commercial Sectors in the Northeast Region of the US
Yunwei Cui, Towson University
11:25 AM
Optimal Congestion Control Strategies for Near-Capacity Urban Metros: Informing Intervention via Fundamental Diagrams
Anupriya -, Imperial College London
CS04 -
Financial Data Applications
Refereed
Wed, Jun 8, 1:15 PM - 2:45 PM
Allegheny Grand Ballroom
Chair(s): Faith (Yueqiao) Zhang, University of Massachusetts Amherst
1:20 PM
Realtime Detection of Bitcoin Bubbles and Estimation of Bubble Formation Time
Min Shu, University of Wisconsin-Stout
1:45 PM
Polynomial Quantile Mixture of Hyperbolic Secant Distribution
Mohan Dev Pant, School of Health Professions, Eastern Virginia Medical School
2:10 PM
Early Warning Signals from Early-Exercise Premia
Ricky Rambharat, Office of the Comptroller of the Currency
CS07 -
Modeling + Non-Parametric Methods
Lightning
Wed, Jun 8, 1:15 PM - 2:45 PM
Fayette
Chair(s): Emily Dodwell, AT&T
1:20 PM
Nonparametric Tests for the Umbrella Alternative in a Mixed Design for a Known Peak
Presentation
Boampong Adu Asare, United Tribes Technical College
1:25 PM
Skeleton Regression: A Graph-Based Approach to Estimation on Manifold
Presentation
Zeyu Wei, University of Washington
1:30 PM
Long-Range Dependence in Low-Frequency Earthquake Catalogs
Presentation
Ariane Ducellier, University of Washington
1:35 PM
Non-parametric identification and estimation of interactions using stochastic intervention target parameters: implications for mixed exposure analysis.
David Brenton McCoy, University of California Berkeley
1:40 PM
Sparse Bayesian Matrix-variate Regression with High-dimensional Data
Hsin-Hsiung Huang, University of Central Florida
1:45 PM
Distribution Free Bootstrap Prediction Intervals After Variable Selection
Lasanthi Watagoda, Appalachian State University
1:50 PM
SMRT: A Structural Model of Latent Ratings and Topics in Text
Desheng Ma, Cornell University
1:55 PM
Alternatives to ANOVA and Regression Amidst Non-normality: Relative Hypothesis Test Performance
Presentation
Anthony J. Bishara, College of Charleston
2:00 PM
Oblique and Non-Linear Survival Trees Based on Dipolar Splitting Criteria
Drew Lazar, Ball State University
2:05 PM
Optimisation of relay team selection for various swimming configurations
Presentation
Gary David Sharp, Nelson Mandela University
2:10 PM
Can a novel human-centered machine learning algorithm predict better than its black-box counterparts? A benchmarking study of transparency-motivated ranked sparsity methods using 66 diverse datasets
Presentation
Ryan Peterson, Colorado School of Public Health
2:15 PM
A Comparison of Time Series Model Fitting using Traditional Time Series Models vs. Deep Learning Models including RNN and LSTM to Stock Market Data of Big Tech Companies in the US
Benjamin Houghton, Georgetown University
PS01 -
Modeling + Non-Parametric Methods, Part 2
Lightning Poster
Wed, Jun 8, 2:45 PM - 3:40 PM
Allegheny I
1
Nonparametric Tests for the Umbrella Alternative in a Mixed Design for a Known Peak
Boampong Adu Asare, United Tribes Technical College
2
Skeleton Regression: A Graph-Based Approach to Estimation on Manifold
Zeyu Wei, University of Washington
3
Long-Range Dependence in Low-Frequency Earthquake Catalogs
Ariane Ducellier, University of Washington
4
Can a novel human-centered machine learning algorithm predict better than its black-box counterparts? A benchmarking study of transparency-motivated ranked sparsity methods using 66 diverse datasets
Ryan Peterson, Colorado School of Public Health
5
Non-parametric identification and estimation of interactions using stochastic intervention target parameters: implications for mixed exposure analysis.
David Brenton McCoy, University of California Berkeley
6
Sparse Bayesian Matrix-variate Regression with High-dimensional Data
Hsin-Hsiung Huang, University of Central Florida
7
Distribution Free Bootstrap Prediction Intervals After Variable Selection
Lasanthi Watagoda, Appalachian State University
8
Oblique and Non-Linear Survival Trees Based on Dipolar Splitting Criteria
Drew Lazar, Ball State University
9
SMRT: A Structural Model of Latent Ratings and Topics in Text
Desheng Ma, Cornell University
10
Alternatives to ANOVA and Regression Amidst Non-normality: Relative Hypothesis Test Performance
Anthony J. Bishara, College of Charleston
11
Optimisation of relay team selection for various swimming configurations
Gary David Sharp, Nelson Mandela University
12
A Comparison of Time Series Model Fitting using Traditional Time Series Models vs. Deep Learning Models including RNN and LSTM to Stock Market Data of Big Tech Companies in the US
Benjamin Houghton, Georgetown University
CS08 -
Classification Methods and Clustering Analysis
Refereed
Wed, Jun 8, 3:45 PM - 5:15 PM
Allegheny Grand Ballroom
Chair(s): Katharine Correia, Amherst College
3:50 PM
A Brief Overview of Explainable and Interpretable AI
Presentation
William Franz Lamberti, University of Virginia
4:15 PM
K-Means Clustering Applied to the Analysis of Wearables and Biosensors from Clinical Trial Data
Vanja Vlajnic, Colorado State University
CS10 -
Applications in Social & Behavioral Sciences
Lightning
Wed, Jun 8, 3:45 PM - 5:15 PM
Fayette
Chair(s): Donna LaLonde, American Statistical Association
3:50 PM
Predicting Census Survey Response Rates via Additive Regression with Interactions
Shibal Ibrahim, MIT
3:55 PM
Partial Association Between Mixed Data: Assessing the Impact of COVID-19 on College Student Well-Being
Zhaohu(Jonathan) Fan, University of Cincinnati
4:00 PM
Does the state-based forward guidance change the way policymakers talk about the outlook and the way nancial markets respond to economic news?
Taeyoung Doh, Federal Reserve Bank of Kansas City
4:05 PM
Modeling the Covid effect on Gasoline Price Changes using Latent Markov Models
Rasitha R Jayasekare, Butler University
4:10 PM
Understanding information about COVID-19: how reliability of used sources and level of understanding influence adherence to sanitary measures in Canada
Presentation
Clémentine Courdi, Université de Montréal
4:15 PM
The Data Mine: Experiential Industry Practicums in Data Science
Presentation
Margaret Betz, Purdue University - The Data Mine
4:20 PM
Data Science Consulting and Collaboration: A Cooperative Adventure
Mara Blake, NC State University Libraries
4:25 PM
Patterns of Mental Health Problems Among General Population Before and After Easing COVID-19 Restrictions
Depeng Jiang, University of Manitoba
4:30 PM
Multivariate time series analysis and forecasting of US unemployment rate
VIJAYKUMAR RAJARAM REDDIAR, CENTRAL CONNECTICUT STATE UNIVERSITY
4:35 PM
A Fast Initial Response Approach to Real-Time Financial Surveillance
Andrews T. Anum, The University of Texas at El Paso
Thursday, June 9
PS02 -
Applications in Social & Behavioral Sciences, Part 2
Lightning Poster
Thu, Jun 9, 9:50 AM - 10:30 AM
Allegheny I
1
Predicting Census Survey Response Rates via Additive Regression with Interactions
Shibal Ibrahim, MIT
2
Partial Association Between Mixed Data: Assessing the Impact of COVID-19 on College Student Well-Being
Zhaohu(Jonathan) Fan, University of Cincinnati
3
Does the state-based forward guidance change the way policymakers talk about the outlook and the way nancial markets respond to economic news?
Taeyoung Doh, Federal Reserve Bank of Kansas City
4
Modeling the Covid effect on Gasoline Price Changes using Latent Markov Models
Rasitha R Jayasekare, Butler University
5
Group-based trajectories and predictors of adherence to four key sanitary measures during the COVID-19 pandemic
Sahar Ramazan Ali, Université de Montréal
6
The Data Mine: Experiential Industry Practicums in Data Science
Margaret Betz, Purdue University - The Data Mine
7
Data Science Consulting and Collaboration: A Cooperative Adventure
Mara Blake, NC State University Libraries
8
Patterns of Mental Health Problems Among General Population Before and After Easing COVID-19 Restrictions
Depeng Jiang, University of Manitoba
9
Multivariate time series analysis and forecasting of US unemployment rate
VIJAYKUMAR RAJARAM REDDIAR, CENTRAL CONNECTICUT STATE UNIVERSITY
10
A Fast Initial Response Approach to Real-Time Financial Surveillance
Andrews T. Anum, The University of Texas at El Paso
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
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
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
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
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
Friday, June 10
CS22 -
Contributions to Model Methods and Applications
Refereed
Fri, Jun 10, 9:00 AM - 10:30 AM
Allegheny Grand Ballroom
Chair(s): Claire Bowen, Urban Institute
9:05 AM
Mixed Effects State Space Models on Research and Development Performance in the New Energy Vehicle Industry
Mingzhao Hu, University of California, Santa Barbara
9:30 AM
Bayesian Nested Latent Class Models for Cause-of-Death Assignment Using Verbal Autopsies Across Multiple Domains
Zehang Li, University of California, Santa Cruz
9:55 AM
High-Dimensional Causal Mediation Analysis Based on Partial Linear Structural Equation Models
Xizhen Cai, Williams College
CS24 -
New Models, Methods, and Applications II
Lightning
Fri, Jun 10, 9:00 AM - 10:30 AM
Cambria
Chair(s): Yaomin Xu, Vanderbilt University Medical Center
9:05 AM
Manifold learning analysis suggests novel strategies to align single-cell multi-modal data of neuronal electrophysiology and transcriptomics
Jiawei Huang, University of Cincinnati
9:10 AM
Spatiotemproal Zero-Inflated Bayesian Negative Binomial Regression Nearest Neighbor Gaussian Process Models
Hsin-Hsiung Huang, University of Central Florida
9:15 AM
Imperfect Imputation: Adjusting for the Error Incurred when We Impute
Presentation
Kyle Frederic Grosser, University of North Carolina at Chapel Hill
9:20 AM
A Case Study with RCT of Varenicline Using Two Machine Learning Approaches
Alondra Cruz, University of California, Los Angeles
9:25 AM
A Brief Review of Blockchain Technology and Impact on Practice of Data Science
David Han, UT San Antonio
9:30 AM
Partial Aggregation Imputation in Geographical Energy Statistics Reporting Networks
Glen Haynes, Energy Information Administration
9:35 AM
On p-value combination of independent and frequent signals
Yusi Fang, Department of Biostatistics, Univertisy of Pittsburgh
9:40 AM
Random Forest Is a Robust Model Choice on Feature Transformed Data for Binary Classification Task
Emma Minasyan, Mimecast
9:45 AM
Ensemble Learning Models for Biomass Estimation and Species Classification of Intertidal Macroalgae Using In-situ and Remote Sensing Spectrometry
Ernst Linder, University of New Hampshire
PS05 -
New Models, Methods, and Applications II, Part 2
Lightning Poster
Fri, Jun 10, 10:30 AM - 11:25 AM
Allegheny I
1
Manifold learning analysis suggests novel strategies to align single-cell multi-modal data of neuronal electrophysiology and transcriptomics
Jiawei Huang, University of Cincinnati
2
Spatiotemproal Zero-Inflated Bayesian Negative Binomial Regression Nearest Neighbor Gaussian Process Models
Hsin-Hsiung Huang, University of Central Florida
3
Imperfect Imputation: Adjusting for the Error Incurred when We Impute
Kyle Frederic Grosser, University of North Carolina at Chapel Hill
4
A Case Study with RCT of Varenicline Using Two Machine Learning Approaches
Alondra Cruz, University of California, Los Angeles
5
A Brief Review of Blockchain Technology and Impact on Practice of Data Science
David Han, UT San Antonio
6
Partial Aggregation Imputation in Geographical Energy Statistics Reporting Networks
Glen Haynes, Energy Information Administration
7
On p-value combination of independent and frequent signals
Yusi Fang, Department of Biostatistics, Univertisy of Pittsburgh
8
Random Forest Is a Robust Model Choice on Feature Transformed Data for Binary Classification Task
Emma Minasyan, Mimecast
9
Ensemble Learning Models for Biomass Estimation and Species Classification of Intertidal Macroalgae Using In-situ and Remote Sensing Spectrometry
Ernst Linder, University of New Hampshire
CS25 -
Methods and Studies to Identify Important Variables
Refereed
Fri, Jun 10, 11:30 AM - 1:00 PM
Butler
Chair(s): Donna LaLonde, American Statistical Association
11:35 AM
Analyzing the Impact of Different Countries’ Approaches to the COVID-19 Pandemic on Their Cumulative Infection Curves by Using Nonparametric Density Regression and Clustering Methods
Presentation
Damian Musk, Stanford OHS
12:00 PM
Water Statistics: A Study Comprehending Several Techniques and Periods at a University
Elisa Henning, Santa Catarina State University
12:25 PM
Partially Constrained Group Variable Selection to Adjust for Complementary Unit Performance in American College Football
Andrey Skripnikov, New College of Florida
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