Key:

Computational Statistics

Data Science Technologies

Data Visualization

Education

Machine Learning

Practice and Applications

Software

Saturday, June 1

Registration
SDSS Hours

Sat, Jun 1, 7:30 AM - 2:00 PM
Grand Ballroom Foyer

GS04 - Fireside Chat
General Session

Sat, Jun 1, 8:30 AM - 9:30 AM
Grand Ballroom E

Chair(s): Gabriela de Queiroz, IBM

New horizons and controversies seem to emerge constantly in the world of statistics and data science. Who can keep up? Our distinguished panel of statistics and data science leaders will discuss this and more in an informal and wide-reaching conversation that contextualizes the SDSS experience with issues of the day.

8:35 AM

Fireside Chat Panel
Amanda Casari, Google Cloud; Amelia McNamara, University of St. Thomas; Mara Averick, RStudio; Miguel Marino, OHSU-PSU School of Public Health

PS06 - Computational Statistics E-Posters
E-Poster

Sat, Jun 1, 9:30 AM - 10:30 AM
Grand Ballroom Foyer

Application of Dynamic Bi-Partite Stochastic Block Models
Neil Hwang, CUNY-Bronx Community College

Estimation of Semiparametric Functional Coefficients Panel Data Model
Shaymal C Halder, Auburn University

Discovery of Gene Regulatory Networks Using Adaptively Selected Gene Perturbation Experiments
Michele Zemplenyi, Harvard University

A Computational Approach to the Structure of Subtraction Games
Kali Lacy, Purdue University

Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems
Presentation Debmalya Nandy, Penn State University

A Data-Adaptive Targeted Learning Approach of Evaluating Viscoelastic Assay Driven Trauma Treatment Protocols
Linqing Wei, UC Berkeley, Department of Biostatistics

Approximate Fiducial Computation and Deep Fiducial Inference
Presentation Gang Li, The University of North Carolina at Chapel Hill

Innovative Robust Boosting Algorithms
Presentation Zhu Wang, UT Health San Antonio

A Model Based Data Fusion Algorithm using Bayesian Hierarchal Modeling for Density Estimation of Rare Species
Purna Gamage, Wake Forest University

Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering
Israel A Almodovar-Rivera, University of Puerto Rico-Medical Science Campus

Developing Nonlinear Genetic Signatures for Enzalutamide Resistance in Prostate Cancer
Isaac Zhao, Brown University

Approximate Bayesian Computational Statistical Methods to Estimate the Strength of Divergent Selection in Yeast
Martyna Lukaszewicz, University of Idaho

Wavelet Shrinkage Using Bayesian False Discovery Rate Methods: a Comparison Study
Presentation Rodney Vasconcelos Fonseca, Unicamp

Analyzing Air Traffic Data with Spark-GraphX
Chathurangi Heshani Pathiravasan, Southern Illinois University, Carbondale

SDSS Teaching Data Science Workshop for High School Teachers
Special Session

Sat, Jun 1, 9:30 AM - 11:30 AM
Regency Ballroom EF

Instructor(s): Shannon Ellis, UC San Diego

Considering how to incorporate data science into your high school STEM classroom?

The goal of this workshop is for you to leave with data science skills and applicable examples that can be used in your classroom.

This workshop will answer questions like:

• What is data science?

• How can high schoolers prepare for data science courses in college?

• What does a career in data science involve?

We will walk through how data scientists carry out projects using RStudio, introduce the basics of the R programming language, and work with real datasets to generate visualizations and analyze data.

Note: Advance sign-up is required, so please see the SDSS 2019 Events page for details!

CS47 - Data Science for Fun
Invited

Sat, Jun 1, 10:00 AM - 11:35 AM
Grand Ballroom E

Organizer(s): David Smith, Microsoft

Chair(s): Ana Bertran, Salesforce

10:05 AM

Minecraft, R, and Containers
Presentation David Smith, Microsoft

10:35 AM

Using Deep Learning in R to Generate Offensive License Plates
Presentation Jacqueline Nolis, Nolis, LLC

CS48 - Recent Advances in Statistical Network Analysis
Invited

Sat, Jun 1, 10:00 AM - 11:35 AM
Grand Ballroom I

Organizer(s): James L Rosenberger, NISS; Lingzhou Xue, Penn State University and NISS

Chair(s): Hyun Bin Kang, Western Michigan University

10:05 AM

Statistical estimation of network models from egocentrically sampled network data
Presentation Jeanette Kurian Birnbaum, University of Washington

10:35 AM

Model-based clustering of large networks
Presentation David Hunter, Penn State University

11:05 AM

Temporal Exponential-Family Random Graph Models with Time-Evolving Latent Block Structure for Dynamic Networks
Kevin Lee, Western Michigan University

CS49 - Computational Efficiency vs. Statistical Guarantee
Invited

Sat, Jun 1, 10:00 AM - 11:35 AM
Grand Ballroom J

Organizer(s): Helen Zhang, University of Arizona

Chair(s): Helen Zhang, University of Arizona

10:05 AM

Embedding Learning
Xiaotong Shen, University of Minnesota

10:35 AM

Penalty Method for Variance Component Selection
Hua Zhou, UCLA

11:05 AM

Distributed Computing for Large Heteroskedastic Spatial Data
Zhengyuan Zhu, Iowa State University

CS50 - Developing Statistical Software For Drug Development
Invited

Sat, Jun 1, 10:00 AM - 11:35 AM
Grand Ballroom K

Organizer(s): Yiming Peng, Genetech

Chair(s): Yiming Peng, Genetech

10:05 AM

Embrace R in Pharma - Building an R Community
Ning Leng, Genentech

10:35 AM

Reproducible Computation at Scale in R
Presentation Will Landau, Eli Lilly and Company

11:05 AM

Leveraging Open Source Tools for Drug Development
Douglas Kelkhoff, Genentech

CS51 - Machine Learning Problems in the Tech Industry
Invited

Sat, Jun 1, 10:00 AM - 11:35 AM
Regency Ballroom AB

Organizer(s): Ryan Tibshirani, Carnegie Mellon University

Chair(s): Ryan Tibshirani, Carnegie Mellon University

10:05 AM

Machine Learning Methods for Estimation and Inference in Differential Networks
Presentation Mladen Kolar, Chicago Booth

10:30 AM

Online and Offline Experimentation in Complex Systems
Presentation Akshay Krishnamurthy, .

10:55 AM

Modern recommendation systems: listwise collaborative ranking and non-stationary contextual bandits
James Sharpnack, UC Davis

11:20 AM

Discussant
Siva Balakrishnan, Carnegie Mellon University

CS52 - Grammar of Graphics: From Theory to Applications
Invited

Sat, Jun 1, 10:00 AM - 11:35 AM
Regency Ballroom C

Organizer(s): Jim Harner, West Virginia University

Chair(s): Zhi Yang, University of Southern California

10:05 AM

Unit Visualizations and the Grammar of Graphics
Presentation Steven Drucker, Microsoft

10:35 AM

ggplot2: An Extensible Platform for Publication-quality Graphics
Presentation Claus Wilke, University of Texas at Austin

11:05 AM

Tableau: Democratizing Visual Analytics by Automating Best Practices
Anushka Anand, Tableau

CS53 - The SAMSI Program on Model Uncertainty
Invited

Sat, Jun 1, 1:00 PM - 2:35 PM
Grand Ballroom I

Organizer(s): David Banks, Duke University / SAMSI

Chair(s): Dongchu Sun, University of Missouri

1:05 PM

The Stochastic Inverse Problem
Lei Yang, SAMSI

1:35 PM

Bayesian Model Calibration and Prediction Applied to Stochastic Simulators
Dave Higdon, Virginia Tech

2:05 PM

Uncertainty Quantification of Stochastic Computer Model for Binary Black Hole Formation
Derek Bingham, Simon Fraser University

CS54 - The IMS Program on Self-Consistency: a Fundamental Statistical Principle for Deriving Computational Algorithims
Invited

Sat, Jun 1, 1:00 PM - 2:35 PM
Grand Ballroom J

Organizer(s): Thomas Lee, UC Davis

Chair(s): Thomas Lee, UC Davis

1:05 PM

Likelihood-Free EM: Self-Consistency for Incomplete or Irregular-Pattern Data
Presentation Xiao-Li Meng, Harvard University

1:35 PM

Latent Variable Models, Self-Consistency, and Stochastic Approximation
Zhiqiang Tan, Rutgers University

2:05 PM

Self-Consistency as a Method to Develop Computationally Effective Algorithms for High-Dimensional Models
Presentation Alex Tsodikov, University of Michigan

CS55 - Recent Advances in Statistical Machine Learning and Reinforcement Learning
Invited

Sat, Jun 1, 1:00 PM - 2:35 PM
Regency Ballroom AB

Organizer(s): Will Wei Sun, University of Miami Business School

Chair(s): Hua Zhou, UCLA

1:05 PM

CORALS: Co-Clustering Analysis via Regularized Alternating Least Squares
Gen Li, Columbia University

1:35 PM

Model-Based Community Detection for Networks with Node Covariates
Ji Zhu, University of Michigan

2:05 PM

Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit
Zheng Wen, Adobe Research

CS56 - Data for Human Health
Contributed

Sat, Jun 1, 1:00 PM - 2:35 PM
Grand Ballroom E

Chair(s): Xiyue Liao, Department of Statistics and Applied Probability, University of California, Santa Barbara

1:05 PM

Multiple-target Robust Design of a Coronary Stent with Multiple Functional Outputs
Presentation Fan JIANG, City University of Hong Kong

1:20 PM

Multiple Hypotheses Testing for Discrete Data - "MHTdicsrete" R package
Yalin Zhu, Merck & Co., Inc.

1:35 PM

What Are the Comorbidities That Go with Asthma? Basket Analysis Approach
Tianyuan Guan, University of Cincinnati

1:50 PM

An Optimal Kernel-Based U-Statistic Method for Quantitative Gene-Set Association Analysis
Tao He, San Francisco State University

2:05 PM

A Nonlinear Hierarchical Modeling Approach to Estimating the BAT Curve Using Markov Chain Monte Carlo
Colin O'Rourke, Benaroya Research Institute

2:20 PM

Floor Discussion

CS57 - Visualization Methods
Contributed

Sat, Jun 1, 1:00 PM - 2:35 PM
Regency Ballroom C

Chair(s): Tiffany Jiang, UC Davis

1:05 PM

Advanced Visualization Techniques for Big Data
Scott Lee Wise, SAS Institute, Inc.

1:20 PM

Interactive Ggplots in R
Presentation Zehao Xu, University of Waterloo

1:35 PM

Visualizing associations of multiple related but distinct phenomena
Presentation Maia P Smith, St George's University

1:50 PM

Data visualization techniques for the analysis of eczema-affected specific regions of the body as predictors of food allergy risk
Presentation Alyssa Ylescupidez, Benaroya Research Institute and the Immune Tolerance Network, Seattle

2:05 PM

Floor Discussion

Hackathon Update
Special Session

Sat, Jun 1, 1:00 PM - 2:35 PM
Regency Ballroom EF

Join the Hackathon participants as they present their findings.

CS58 - When Biomedical Data Gets Big: Challenges and Solutions in Biomedical Data Science
Invited

Sat, Jun 1, 2:45 PM - 3:50 PM
Grand Ballroom E

Organizer(s): James Eddy, Sage Bionetworks

Chair(s): Yalin Zhu, Merck & Co., Inc.

2:50 PM

Analysis of Whole Genome Sequence Analysis in >100k Individuals: Experience in the TOPMed Program
Ken Rice, Universiry of Washington

3:20 PM

Biomedical Informatics and Precision Medicine Are Laying the Framework for the Next Generation of Data-Driven Clinical Research
Sean Mooney, University of Washington

CS59 - Data Science Platforms: Docker and Kubernetes
Invited

Sat, Jun 1, 2:45 PM - 3:50 PM
Grand Ballroom I

Organizer(s): Jim Harner, West Virginia University

Chair(s): Sirish Shrestha, West Virginia University

2:50 PM

RsparkHub: Scaling Rspark with Kubernetes
Jim Harner, West Virginia University

3:20 PM

Using Rocker Containers and CI for Teaching R-Based Courses
Presentation Colin Wiiter Rundel, Duke University

CS60 - Expanding the Toolkit for Teaching Statistics
Invited

Sat, Jun 1, 2:45 PM - 3:50 PM
Regency Ballroom EF

Organizer(s): Alicia Johnson, Macalester College

Chair(s): Mikael Vejdemo-Johansson, CUNY College of Staten Island

2:50 PM

(A Picture-Book Approach To) Teaching the Analytics Process
Ruth M Hummel, SAS Institute / JMP Division

3:20 PM

Teaching Data Science Using Jupyter Notebooks and Binder
Presentation Brian Kim, University of Maryland

CS61 - Advances in Regression and Modeling
Contributed

Sat, Jun 1, 2:45 PM - 3:50 PM
Grand Ballroom J

Chair(s): Yongli Sang, University of Louisiana at Lafayette

2:50 PM

Nonparametric Estimation of a Mixing Distribution for Pharmacokinetic Stochastic Models
Alona Kryshchenko, California State University Cannel Islands

3:20 PM

Floor Discussion

CS62 - New Developments in Statistical Learning
Contributed

Sat, Jun 1, 2:45 PM - 3:50 PM
Regency Ballroom AB

Chair(s): Gen Li, Columbia University

2:50 PM

Flexible Functional Specification in Hierarchical Bayesian Estimation of Discrete Choices
Kali (Duke) Chowdhury, University of California, Irvine

3:05 PM

Correlation Tensor Decomposition and Its Application in Spatial Imaging Data
Yujia Deng, University of Illinois, Urbana-Champaign

3:20 PM

INDIVIDUALIZED MULTI-DIRECTIONAL VARIABLE SELECTION
Xiwei Tang, University of Virginia

3:35 PM

Quantile Regression for Big Data with Small Memory
Yichen Zhang, New York University

GS05 - Closing Keynote Address
General Session

Sat, Jun 1, 4:00 PM - 5:00 PM
Grand Ballroom E

Organizer(s): Kelly McConville, Reed College

Chair(s): Tim Hesterberg, Google

4:05 PM

Data Science and Statistics: Let's Not Call the Whole Thing Off!
Daniela Witten, University of Washington

Online Program

Key:

ASA Meetings Department