Viewing Track 'Data Science Techologies' only

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Computational Statistics

Data Science Technologies

Data Visualization

Education

Machine Learning

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Thursday, May 30

CS05 - Scaling Up Machine Learning to Production
Invited

Thu, May 30, 10:30 AM - 12:05 PM
Regency Ballroom AB

Organizer(s): Jim Harner, West Virginia University

Chair(s): Jim Harner, West Virginia University

10:35 AM

'ML Ops' and Productionizing Machine Learning Workflows
Amy Unruh, Google

11:05 AM

TFX: Production ML Pipelines with TensorFlow
Robert Crowe, Google

11:35 AM

Scalable Automatic Machine Learning with H2O
Erin LeDell, H2O.ai

CS09 - Project Jupyter
Invited

Thu, May 30, 1:30 PM - 3:05 PM
Regency Ballroom AB

Organizer(s): Brian Granger, Cal Poly; Fernando Perez, UC Berkeley

Chair(s): Casey Jelsema, West Virginia University

1:35 PM

Sharing Reproducible Computations on Binder
Presentation Lindsey J. Heagy, UC Berkeley

2:05 PM

Open Infrastructure in the Cloud with JupyterHub
Chris Holdgraf, UC Berkeley

2:35 PM

JupyterLab: An Extensible and Flexible Platform for Collaborative Data Science
Brian Ellison Granger, Cal Poly / Project Jupyter

PS02 - Data Science Applications E-Posters, I
E-Poster

Thu, May 30, 3:00 PM - 4:00 PM
Grand Ballroom Foyer

Automated Survey Text Analysis -- Supervised Latent Dirichlet Allocation (SLDA)
Presentation Christine P. Chai, Microsoft

Comparing various string similarity algorithms in the task of name-matching
Presentation Aleksandra Zaba, University of Utah

Hypothesis Testing in Nonlinear Function on Scalar Regression with Application to Child Growth Study
Mityl Biswas, NC State University

Comparing Object Correlation Metrics for Effective Space Traffic Management
Julie Zhang, University of Washington

Batch effect adjustment via ensemble learning in the validation of genomic classifiers
Yuqing Zhang, Boston University

Tensor Mixed Effects Model with Application to Nanomanufacturing Inspection
Presentation Xiaowei Yue, Virginia Polytechnic Institute and State University

Burst Detection in Call Trains for Identifying Fraud in Telecommunications
Presentation Miguel Raul Pebes Trujillo, Indiana University Bloomington, Department of Statistics

Active Labeling using Model-based Classification
Min Fang, San Jose State University

Analyzing Influence of Social Media Through Twitter
Presentation Dhrubajyoti Ghosh, North Carolina State University

Diversity of forest structure across the United States
Jessica Lynn Gilbert, Purdue University

ClusterJob, an Experiment Management System For Ambitious Data Science
Bekk Blando, Clemson University

A Maximum Likelihood Method for Correlated Discrete and Continuous Outcomes with Selection, Lagged Effects and Variance
Rhoda Nandai Muse, University of Arizona, Mathematics Department

Gender Distribution in Movie Roles
Presentation Vijay Ravuri, CalPoly SLO

Evaluating and forecasting the CD4 cell count evolution in HIV+ patients from a Bayesian stochastic model related to the logistic curve with multiple inflection points.
Victor Cruz-Torres, University of Puerto Rico

CS17 - Shared Infrastructure for Data Science
Invited

Thu, May 30, 4:00 PM - 5:35 PM
Regency Ballroom AB

Organizer(s): Soren Harner, Permaling

Chair(s): James Sharpnack, UC Davis

4:05 PM

The Machine Learning Lifecycle with MLflow
Siddharth Murching, Databricks, Inc.

4:35 PM

Low-Latency Model Serving with MLflow and MLeap
Corey Zumar, Databricks, Inc.

5:05 PM

Bayesian Structured Time Series in TensorFlow Probability
Jacob Burnim, Google

PS03 - Data Science Applications E-Posters, II
E-Poster

Thu, May 30, 5:30 PM - 6:30 PM
Grand Ballroom Foyer

Automated Analytics of the Solar Corona with Scalable Cloud Based Platforms
Lars K. S. Daldorff, JHU/APL

Modeling and Forecasting the Percent Changes in the National Park Visitation Counts Using Social Media Data
Russell Goebel, Western Washington University

Estimating Plant Growth Curves and Derivatives by Modeling Crowdsourced Imaged-Based Data
Haozhe Zhang, Iowa State University

Using Bayesian Networks to Perform Reject Inference
Billie Anderson, Harrisburg University

Usability evaluation of data presentation for official statistics
Presentation Lin Wang, U.S. Census Bureau

Do Unregistered Voters Want to Vote? Automatic Registration and Oregon Elections Turnout.
Matthew Stephan Yancheff, Reed College

Relationship between physical activity and depression in elderly Costa Ricans
Presentation Shu Li, Kent State University

Building an Interpretable Incident Prediction model for Site Reliability
Jiaping Zhang, Salesforce

For-estimation: Post-stratification to increase efficiency of forest attribute estimates
Miranda Rintoul, Reed College

Forecasting NBA Fan Support using Time Series Analysis
Victor Wilson, Cal Poly San Luis Obispo

Handling Missing Data in Cardiovascular Disease Prediction Using Neural Networks
Presentation Megan Shand, Broad Institute

Leverage Machine Learning to Advance Risk Prediction with Electronic Health Record
Presentation Yirui Hu, Geisinger

Multiple uses for chronic condition data mart
John Massman, Virginia Mason

Team Item Response Models
Deborshee Sen, Duke University

Friday, May 31

CS20 - Data Science Platforms: Spark
Invited

Fri, May 31, 10:30 AM - 12:05 PM
Grand Ballroom E

Organizer(s): Kevin Kuo, RStudio

Chair(s): Kevin Kuo, RStudio

10:35 AM

An R Interface to Hail
Presentation Michael Lawrence, Genentech Research

11:05 AM

Scaling Sparklyr with Streams and Arrow
Javier Luraschi, RStudio

11:35 AM

Interpretable Machine Learning Using rsparkling
Navdeep Gill, H2O.ai

CS27 - Data Science Platforms: Deep Learning
Invited

Fri, May 31, 1:30 PM - 3:05 PM
Grand Ballroom E

Organizer(s): Javier Luraschi, RStudio

Chair(s): Javier Luraschi, RStudio

1:35 PM

Deep Learning and Probabilistic Programming with Applications to Intelligent Reality
Soren Harner, Permaling

2:05 PM

R Interfaces to TensorFlow and Keras
Kevin Kuo, RStudio

2:35 PM

Deep Learning Models at Scale with Apache Spark
Presentation Joseph Kurata Bradley, Databricks, Inc.

CS33 - Backend Data Science
Invited

Fri, May 31, 3:40 PM - 5:15 PM
Grand Ballroom E

Organizer(s): Edgar Ruiz, RStudio

Chair(s): Soren Harner, Permaling

3:45 PM

Data Science with Databases and R
James Blair, RStudio

4:15 PM

STOIC Next-Generation Spreadsheet: Bringing Data Science to the Masses
Ismael Ghalimi, STOIC

4:45 PM

Working with Images and Text in R Through Embeddings
Michael Lucy, Basilica

CS40 - SAS Open-Source Platforms for Analytics
Invited

Fri, May 31, 5:20 PM - 6:25 PM
Grand Ballroom E

Organizer(s): Jim Harner, West Virginia University

Chair(s): Wendy Martinez, Bureau of Labor Statistics

5:25 PM

SAS Viya: A Modern Scalable and Open Platform for Artificial Intelligence
Presentation Wayne Thompson, SAS

5:55 PM

Making Predictive Modeling Approachable with JMP Pro
Jordan Hiller, JMP

Saturday, June 1

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

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

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

Online Program

Viewing Track 'Data Science Techologies' only

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