Workshop 1 – Data Visualization

Xijin Ge, South Dakota State University

Pasque 255

1:00 PM - 5:00 PM

Workshop 2 – Web Crawling

Peter Claussen, South Dakota State University

Dakota Room 250 A/C

1:00 PM - 5:00 PM

Workshop 3 – R Library Creation Fundamentals

Md Riaz Khan

Dakota Room 250 A/C

1:00 PM - 5:00 PM

Session 2 - Opportunities for Improving Health through Big Data and Data Science: Data Science Infrastructure in the Cloud for Sanford Imagenetics, a Population Scale Genetic Medicine Initiative

Murat Sincan, Sanford Imaginetics

Pheasant Room 253 A/B

9:30 AM - 10:30 AM

Session 2 - Opportunities for Improving Health through Big Data and Data Science: Data-Drivin Healthcare: The Sanford Data Collaborative

Arielle Selya, Sanford Research

Pheasant Room 253 A/B

9:30 AM - 10:30 AM

Session 3 - Precision Agriculture: Imputing Data without Replication

Jixiang Wu, South Dakota State University

Dakota Room 250 A/C

9:30 AM - 10:25 AM

Session 3 - Precision Agriculture: Multi-Resolution Approximations for Precision Agriculture

Paul May, South Dakota State University
Hossein Moradi, South Dakota State University

Dakota Room 250 A/C

9:30 AM - 10:30 AM

Session 3 - Precision Agriculture: Towards Deep Learning for Weed Detection: Deep Convolutional Neural Networks Architectures for Plant Seedling Classification

Martinson Ofori, Dakota State University
Omar El-Gayar, Dakota State University

Dakota Room 250 A/C

9:30 AM - 10:30 AM

Session 4 - Advances in Probabilistic Modeling for Machine Learning: An Approach to Initializing the EM Algorithm in Gaussian Mixtures with an Unknown Number of Components

Igor Melnykov, University of Minnesota - Duluth

Campanile & Hobo Day Gallery (A & B)

9:30 AM - 10:30 AM

Session 4 - Advances in Probabilistic Modeling for Machine Learning: Gaussian Mixture Modeling and Model-based Clustering under Measurement Inconsistency

Rong Zheng, Western Illinois University

Campanile & Hobo Day Gallery (A & B)

9:30 AM - 10:30 AM

Session 4 - Advances in Probabilistic Modeling for Machine Learning: On Finite Mixture Modeling of Change-point Processes

Yana Melnykov, University of Alabama - Tuscaloosa

Campanile & Hobo Day Gallery (A & B)

9:30 AM - 10:30 AM

Session 4 - Advances in Probabilistic Modeling for Machine Learning: Semiparametric Imputation using Conditional Gaussian Mixture Models

Danhyang Lee, University of Alabama - Tuscaloosa

Campanile & Hobo Day Gallery (A & B)

9:30 AM - 10:30 AM

Session 2 - Opportunities for Improving Health through Big Data and Data Science: Propensity Score Methods for Reducing Bias in Observational Studies: An Example from the PRAMS Study

Sooyong Kim, Sanford Research

Pheasant Room 253 A/B

11:00 AM - 12:00 PM

Session 2: Opportunities for Improving Health through Big Data and Data Science: Floor Discussion

Arielle Selya, Sanford Research

Pheasant Room 253 A/B

11:00 AM - 12:00 PM

Session 5 - Natural Language Processing: A Simple Introduction to Natural Language Processing and Its Clinical Applications in the Era of Artificial Intelligence

Yanshan Wang, Mayo Clinic

Dakota Room 250 A/C

11:00 AM - 12:00 PM

Session 5 - Natural Language Processing: Large-window Techniques for Geospatial Raster Data

Anne Denton, North Dakota State University--Fargo

Dakota Room 250 A/C

11:00 AM - 12:00 PM

Session 6 - Nonparametric Methods for Data Science: Asymptotically Distribution-free Change-Point Detection for Non-Euclidean and Multivariate Data

Lynna Chu, Iowa State University

Campanile & Hobo Day Gallery (A & B)

11:00 AM - 12:00 PM

Session 6 - Nonparametric Methods for Data Science: Some of These Things is Not Like the Others: Visual Statistics and Testing in Statistical Graphics

Susan Vanderplas, University of Nebraska - Lincoln

Campanile & Hobo Day Gallery (A & B)

11:00 AM - 12:00 PM

Session 6 - Nonparametric Methods for Data Science: The Development of Pairwise Sample Comparison Methods of Particle Micromorphometry of AL Powders for Nearest Neighbor Classifiers

Cami Fuglsby, South Dakota State University

Campanile & Hobo Day Gallery (A & B)

11:00 AM - 12:00 PM

Poster Session: Student Poster Competition

South Dakota State University

Volstorff A

1:00 PM - 2:00 PM

Session 11 - Methods: Stress-strength Inference for the Multicomponent System Based on Progressively type-II Censored Samples from Pareto Distributions

Lauren Sauer, University of South Dakota

Campanile & Hobo Day Gallery (A & B)

2:30 PM - 3:25 PM

Session 7 - Application: Speed Session by Grad Students

Rajesh Godasu, Dakota State University
Lawrence Segbehoe, South Dakota State University
Josh Eason, Creighton University
Ganga Basyal, Dakota State University
Ayorinde Ogunyiola, South Dakota State University
Omar Sharif, University of South Dakota

Pasque 255

2:30 PM - 10:25 AM

Session 8 - Tools: Introduction to Git and Github

Seema Bhandari, Dakota State University

Pheasant Room 253 A/B

2:30 PM - 3:25 PM

Session 8 - Tools: Jupyter Notebook & Python for Data Scientists

David Zeng, Dakota State University

Pheasant Room 253 A/B

2:30 PM - 3:25 PM

Session 9 - Forecasting: Data Science in the Life Insurance Industry

Gary Hatfield, Securian Financial Group

Dakota Room 250 A/C

2:30 PM - 3:25 PM

Session 9 - Forecasting: Multi-Step Forecast of the Implied Volatility Surface Using Deep Learning

Zhiguang Wang, South Dakota State University

Dakota Room 250 A/C

2:30 PM - 3:25 PM

Session 9 - Forecasting: Using Prophet Methodology for Forecasting

Ally Pelletier, Polaris Industries

Dakota Room 250 A/C

2:30 PM - 3:25 PM

Session 13 - Data Science and Startups: Get Answers and Insights from your Data

Dhiraj Sharan, Query AI

Dakota Room 250 A/C

3:30 PM - 4:30 PM

Session 14 - Healthcare: A Dense-Inception Network for Medical Image Classification

James Boit, Dakota State University
David Zeng, Dakota State University

Campanile & Hobo Day Gallery (A & B)

3:30 PM - 4:30 PM

Session 14 - Healthcare: A Patient-Centered Approach to IT Enabled Diabetes Self-Management: The Case of Saudi Arabia

Hassan Alyami, Dakota State University

Campanile & Hobo Day Gallery (A & B)

3:30 PM - 4:30 PM

Session 14 - Healthcare: Exploring Task Decomposition with Ensemble Approach using Reinforcement Learning

Raisa Nusrat, University of South Dakota
Daniel Elliott, University of South Dakota
KC Santosh, University of South Dakota

Campanile & Hobo Day Gallery (A & B)

3:30 PM - 4:30 PM