PMED Transition Workshop: May 20-21, 2019

** The deadline for applications was April 19, 2019 **


This workshop will be held at SAS Hall on the campus of NC State University.


The transition workshop for the PMED program is an opportunity for the active working groups in the program to exchange results and share their perspectives on common issues. This workshop is focused on recent research progress that has been made in connection with the many research areas spanned by the PMED program. Sessions of talks dedicated to each working group will be presented by active members. The workshop’s goal is to facilitate planning for continuing collaborations on further research questions to extend beyond the period of the PMED program.

** Planning for this event is ongoing **

** Notice of Consent **

SAMSI values the proprietary and intellectual property of our participants. The materials presented at our various workshops and programs are in high demand by event participants and the applied mathematics and statistics community that comprise our audience. Therefore, we encourage all of our invited speakers to share their materials, as appropriate, in order to pass along the valuable research that is being done in your field of study and is a focus of this event. In addition, unless SAMSI is give written approval from our speakers we ARE NOT authorized to share the materials presented at this event.

Please click HERE to complete a SAMSI Consent form for this event. SAMSI appreciates your time and willingness to share this valuable content with others and we hope you enjoy this event!
For any questions or concerns about our consent policy, please contact us at:

Schedule and Supporting Media

Printed Schedule

Monday, May 20, 2019
Room 1102, SAS Hall, N.C. State University, Raleigh, NC


Time Description Speaker Slides
Theme 1 (Tumor Heterogeneity)
9:00-9:15am Intro and Overview on Tumor Heterogeneity Working Group Kevin Flores, N.C. State University
John Nardini, SAMSI & N.C. State University
9:15-9:45am Virtual Tumor Populations from a Randomized Reaction-Diffusion Modely Nick Henscheid, University of Arizona
9:45-10:15am Nonlinear Mixed Effects Models Applied to Tumor Heterogeneity Rebecca Everett, N.C. State University
10:15-10:30am BREAK
10:30-10:45am Creating Virtual Populations for Modeling Tumor Heterogeneity John Nardini, SAMSI & N.C. State University
10:45-11:15am Applications of Machine Learning to Heterogeneous Population Data John Lagergren, N.C. State University
11:15-11:45am Non-parametric Techniques for Estimating Tumor Heterogeneity Erica Rutter, N.C. State University
11:45am-1:30pm LUNCH (on own)
Theme 2 (Sequential Decision Making (Observational Data))
Session title: Real World Challenges in Observational Data DTR Analyses
1:30-1:45pm Intro and Overview on Theme 2 Erica Moodie, McGill University
1:45-2:15pm Dynamic Treatment Regimes via Reward Ignorant Modeling Michael Wallace, University of Waterloo
2:15-2:45pm Using Inverse Conditional Probability Weights to Adjust for Unmeasured Cluster-Specific Confounding in Clustered Data Zulin He, Iowa State University
2:45-3:15pm Estimation and Optimization of Composite Outcomes Daniel Luckett, University of North Carolina, Chapel Hill
3:15-3:45pm BREAK
Theme 3 (Observational Microbiome)
3:45-4:00pm Introduction to the Observational Microbiome Working Group Session Li Ma, Duke University
4:00-4:30pm Network Methods for Integrating Compositional Microbiome Data with Machine Learning Andrew Hinton, University of North Carolina, Chapel Hill
4:30-5:00pm Bayesian Graphical Compositional Regression for Microbiome Data Jialiang Mao, Duke University
5:00-5:30pm MIMIX: a Bayesian Mixed-Effects Model for Microbiome Data from Designed Experiments Brian Reich, N.C. State University
5:45pm Return to Hotel

Tuesday, May 21, 2019
Room 1102, SAS Hall, N.C. State University, Raleigh, NC

Time Description Speaker Slides
9:15-10:15am Plenary Talk 1: A Bayesian Model for Joint Longitudinal and Survival Outcomes in the Presence of Subpopulation Heterogeneity Elizabeth Slate, Florida State University
10:15-10:30am BREAK
10:30-11:30am Plenary Talk 2: Some Recent Advances in Precision Medicine and Machine Learning Michael Kosorok, University of North Carolina, Chapel Hill
11:30am-12:30pm Plenary Talk 3: Machine Learning Methods to Learn Improved Electrophysiological Biomarkers in Clinical Trials David Carlson, Duke University
12:30pm Adjourn
Shuttle to RDU Airport

Questions: email