Online Program
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Key:
Computational Statistics
Data Science Technologies
Data Visualization
Education
Machine Learning
Practice and Applications
Software
Friday, May 31
Friday Keynote Address
General Session
Fri, May 31, 8:30 AM - 10:00 AM
Organizer(s): Kelly McConville, Reed College
Data Science: How the Union of Inferential Thinking and Computation Are Transforming Research and Education at Berkeley
Fernando Perez, UC Berkeley
Data Science Platforms: Spark
Invited
Fri, May 31, 10:30 AM - 12:00 PM
Organizer(s): Kevin Kuo, RStudio
Chair(s): Kevin Kuo, RStudio
An R Interface to Hail
Michael Lawrence, Genentech Research
Scaling Sparklyr with Streams and Arrow
Javier Luraschi, RStudio
Using H2O in Spark with R
Navdeep Gill, H2O.ai
Advances in Analysis and Computing in Complex Data
Invited
Fri, May 31, 10:30 AM - 12:00 PM
Organizer(s): George Michailidis, University of Florida
Chair(s): Regina Liu, Rutgers University
Graph-Based Change-Point Detection
Hao Chen, UC Davis
A Double Core Tensor Factorization and Its Applications to Heterogeneous Data
George Michailidis, University of Florida
Individualized Fusion Learning (IFusion) with Applications to Personalized Inference
Minge Xie, Rutgers University
Building and Growing Data Science Teams
Invited
Fri, May 31, 10:30 AM - 12:00 PM
Organizer(s): Jacqueline Nolis, Nolis, LLC
From Zero to A^X: Scaling Data Science Teams
Amanda Casari, Google Cloud
Together at Last: Heterogeneous Teams and the Key to Success
Heather Nolis, T-Mobile
Creating Effective Data Science Teams
Mehar Singh, ProCogia
Recent Developments on Machine Learning
Invited
Fri, May 31, 10:30 AM - 12:00 PM
Organizer(s): Xiaotong Shen, University of Minnesota
Chair(s): Xiaotong Shen, University of Minnesota
Shrinking Characteristics of Precision Matrix Estimators
Adam J. Rothman, University of Minnesota
P-Splines with an L1 Penalty for Repeated Measures
Hui Jiang, University of Michigan
Community Detection with Dependent Connectivity
Annie Qu, University Illinois at Urbana-Champaign
A Field Guide to Education Tools in Data Science
Invited
Fri, May 31, 10:30 AM - 12:00 PM
Organizer(s): Alison Hill, RStudio
Chair(s): Alison Hill, RStudio
Experiences in Teaching Data Science and Visualization at NASA
David Meza, NASA
Necessity Is the Mother of Invention: Evolution of a Data Science Team
Adrienne Zell, Oregon Health and Science University
Data Visualization Education
Invited
Fri, May 31, 1:30 PM - 3:00 PM
Organizer(s): Silas Bergen, Winona State University; Amelia McNamara, University of St. Thomas
Teaching Data Visualization: Integrating Theory and Practice
Michael Freeman, University of Washington
A Three-Part Data Visualization Curriculum
Jerzy Wieczorek, Colby College
Help Me Understand: Guiding Visualization Users with Annotations
Robert Kosara, Tableau Software
Data Science Ethics Meet Reality
Invited
Fri, May 31, 1:30 PM - 3:00 PM
Organizer(s): Os Keyes, University of Washington
The Politics of Data
Os Keyes, University of Washington
The Political Consequences of Repurposing Data
Meg Young, University of Washington
Beyond Methodological Rigor: Widening the Scope of Ethics in Data Science
Anissa Tanweer, University of Washington
The Cutting Edge in Statistical Machine Learning
Invited
Fri, May 31, 1:30 PM - 3:00 PM
Organizer(s): Daniela Witten, University of Washington
Chair(s): Daniela Witten, University of Washington
A Continuous-Time View of Early Stopping in Least Squares Regression
Ryan Tibshirani, Carnegie Mellon University
Fused Lasso on Graphs: Applications to Nonparametric Statistical Problems
Oscar Hernan Madrid Padilla, UC Berkeley
Two-Stage Computational Framework for Sparse Generalized Eigenvalue Problem
Kean Ming Tan, University of Minnesota
Data Science Platforms: Deep Learning
Invited
Fri, May 31, 1:30 PM - 3:00 PM
Organizer(s): Javier Luraschi, RStudio
Deep Learning and Probabilistic Programming with Applications to Intelligent Reality
Soren Harner, Permaling
R Interfaces to TensorFlow and Keras
Kevin Kuo, RStudio
Deep Learning Models at Scale with Apache Spark
Joseph Kurata Bradley, Databricks, Inc.
Backend Data Science
Invited
Fri, May 31, 3:30 PM - 5:00 PM
Organizer(s): Edgar Ruiz, RStudio
Data Science with Databases and R
Edgar Ruiz, RStudio
STOIC Next-Generation Spreadsheet: Bringing Data Science to the Masses
Ismael Ghalimi, STOIC
Working with Images and Text in R Through Embeddings
Michael Lucy, Basilica
Computational Statistics for Large-Scale Biological Data
Invited
Fri, May 31, 3:30 PM - 5:00 PM
Organizer(s): Jacob Bien, University of Southern California
Chair(s): Kean Ming Tan, University of Minnesota
Computationally Efficient High-Dimensional Interaction Modeling
Guo Yu, University of Washington
Inference for Diversity Under Networked Models
Amy Willis, University of Washington
Variance Component Testing and Selection for a Longitudinal Microbiome Study
Jin Zhou, University of Arizona
Democratizing Data Science with Workflows
Invited
Fri, May 31, 3:30 PM - 5:00 PM
Organizer(s): Michael I. Love, UNC-Chapel Hill
Publishing Literate Programming Workflows in Scientific Journals
Michael I. Love, UNC-Chapel Hill
When Should You Add Github, Make and Docker to Your Data Science Workflow?
Tiffany Timbers, University of British Columbia
Useful Tools for Teaching and Outreach in Data Science: Workflows, Case Studies, Github Classroom, and Slack
Stephanie Hicks, Johns Hopkins Bloomberg School of Public Health
Modern Multivariate Analysis
Invited
Fri, May 31, 3:30 PM - 5:00 PM
Organizer(s): Adam J. Rothman, University of Minnesota
The Multivariate Square Root Lasso: Computational and Theoretical Insights
Aaron Molstad, Fred Hutchinson Cancer Research Center
Estimating Multiple Precision Matrices Using Cluster Fusion Regularization
Brad Price, West Virginia University
$L_2$-Regularization and Some Path-Following Algorithms
Yunzhang Zhu, The Ohio State University
Data Visualizations at the Institute for Health Metrics and Evaluation
Invited
Fri, May 31, 3:30 PM - 5:00 PM
Organizer(s): Brian Dart, IHME
Building Interactive Data Visualization for a Global (Health) Audience
Ryan Shackleton, University of Washington
The Story of a Chart: Data Visualization Principles to Simplify Complexity
Evan Laurie, University of Washington
Behind the Scenes: Building Tools to Visualize Intermediate Results in Complex Data Science Pipelines
Marlena Bannick, University of Washington
Incorporating Ethics and Inclusion in Undergraduate Statistics Curriculum
Invited
Fri, May 31, 5:15 PM - 6:15 PM
Organizer(s): Brianna Heggeseth, Macalester College
Ethics in an Advanced Undergraduate Seminar: Statistical Analysis of Social Network Data
Miles Q. Ott, Smith College
Intertwining Data Ethics into Intro Stats
Brianna Heggeseth, Macalester College
Grammar of Graphics: The Twentieth Anniversary
Invited
Fri, May 31, 5:15 PM - 6:15 PM
Organizer(s): Jim Harner, West Virginia University
Past, Present, and Future of Grammar of Graphics Systems
Lee Wilkinson, H2O.ai
Interoperability: Your R Package Can Depend on Its Friends
Invited
Fri, May 31, 5:15 PM - 6:15 PM
Organizer(s): Matthew N. McCall, University of Rochester
Case Studies in Interoperability: From Generic Classes to Specific Functions
Matthew N. McCall, University of Rochester
How Core Data Structures Drive Interoperability in the Bioconductor Project
Levi Waldron, CUNY SPH.
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