Thursday October 1

The Michigan League, 2nd floor, Vandenberg Room

5:00pm            Registration opens

6:00-8:00pm   Poster session and reception

Friday October 2

Rackham Graduate School, 4th floor

8:15am  Registration and breakfast

8:50am  Opening remarks:  Xuming He

Session 1, chair Xuming He

9:00-9:30am Karen Kafadar, University of Virginia   
Contributions to Industrial Statistics and their Impact on Medical Screening

9:30-10:00am William Cleveland, Purdue University 
Divide & Recombine with Tessera: High Performance Computing for Data Analysis

10:00-10:30am  Trevor Hastie, Stanford University
GAM selection via convex optimization

10:30-11:00am  Coffee break

Session 2, chair Shuheng Zhou

12:30-2:00pm Lunch break (on your own)

Session 3, chair Long Nguyen

2:00- 2:25pm  Earl Lawrence, Los Alamos National Labs
An In Situ Approach to Partitioning a Complex Simulation

2:25-2:50pm Roshan Vengazhiyil, Georgia Tech
Uncertainty Quantification and Robust Parameter Design in Machining Simulations

2:50-3:15pm Judy Jin, University of Michigan 
Signals by Integrating ICA and SCA Methods

3:15-3:40pm Casey Diekman, New Jersey Institute of Technology  
Discovering Functional Neuronal Connectivity from Serial Patterns in Spike Train Data

3:40-4:10pm Coffee break

Session 4, chair Susan Murphy

4:10-4:40pm Eric Laber, North Carolina State University  
Online estimation of optimal treatment allocation strategies

4:40-5:10pm  Nalini Ravishanker, University of Connecticut  
Clustering Sets of Nonlinear and Nonstationary Time Series

5:10-5:40pm Kwok Leung Tsui, City University of Hong Kong   
Evolution of Big Data Analytics

6:00pm Conference banquet   Campus Inn, 615 E. Huron St., Regency Ballroom
(drinks and hors d’oeuvres served from 6:00pm, sit down dinner at 7pm)

Saturday October 3

Rackham Graduate School, 4th floor

Session 5, chair Kerby Shedden

9:00-9:30am  Jianjun Shi, Georgia Tech  
Statistics Methods Driven by Engineering Model for System Performance Improvement

9:30-10:00am  Derek Bingham, Simon Fraser University  
Prediction Using Outputs From Multi-fidelity Simulators

10:00-10:30am  David Higdon, Virginia Tech   
Connecting Model-Based Predictions to Reality

10:30-11:00am  Coffee break

Session 6, chair Liza Levina

11:00-11:30am  Peter Bickel, UC Berkeley  
Identifying Erdos-Renyi nodes in block models 

11:30-12:00pm  Kjell Doksum, University of Wisconsin, Madison   
Perspectives on small and large data

12:00-12:30pm  Jerry Lawless, University of Waterloo  
Big Data and Scientific Inference

12:30-2:00pm   Lunch at the Michigan League, 2nd floor, Hussey room  (included with registration)

Session 7, chair Ji Zhu

2:00-2:25pm  Xiao Wang, Purdue University   
Optimal Estimation for the Functional Cox Model

2:25-2:50pm  Adam Rothman, University of Minnesota  
Indirect multivariate response linear regression

2:50-3:15pm  Bowei Xi, Purdue University  
Adversarial Data Mining

3:15-3:40pm  Aijun Zhang, Hong Kong Baptist University  
Big Data Analytics in Online Education

3:40pm Closing remarks