Biometrics Section Announces 2017 Award Winners

The David P. Byar Young Investigator Award is given annually to a new researcher in the Biometrics Section who presents an original manuscript at the Joint Statistical Meetings. The award commemorates David Byar, a renowned biostatistician who made significant contributions to the development and application of statistical methods during his career at the National Cancer Institute. In addition, the section gives travel awards. This year, we had 52 submissions to the paper competition. We are pleased to announce the following recipients:

David P. Byar Young Investigator Award

Edward Kennedy, Carnegie Mellon University, “Robust Estimation and Inference for the Local Instrumental Variable Curve”

Travel Awards 
  • Joseph Antonelli, Harvard T.H. Chan School of Public Health, “Double Robust Matching Estimators for High-Dimensional Confounding Adjustment”
  • Qingpo Cai, Emory University, “Bayesian Variable Selection Over Large-Scale Networks via the Thresholded Graph Laplacian Gaussian Prior with Application to Genomics”
  • Anqi Cheng, University of Washington, “Monotone Distribution Function Estimation in Randomized Trials with Noncompliance”
  • Wenting Cheng, University of Michigan, “Informing a Risk Prediction Model for Binary Outcomes with External Coefficient Information”
  • Chanmin Kim, Harvard T.H. Chan School of Public Health, “Bayesian Methods for Multiple Mediators: Relating Principal Stratification and Causal Mediation in the Analysis of Power Plant Emission Controls”
  • Shelley H. Liu, Harvard T.H. Chan School of Public Health, “Lagged Kernel Machine Regression for Identifying Time Windows of Susceptibility to Exposures of Complex Metal Mixtures”
  • Krithika Suresh, University of Michigan, “Comparison of Joint Modeling and Landmarking for Dynamic Prediction Under an Illness-Death Model”
  • Guan Yu, State University of New York at Buffalo, “Optimal Sparse Linear Prediction for Block-Missing Multi-Modality Data Without Imputation”
  • Xiang Zhan, Fred Hutchinson Cancer Research Center, “A Fast Small-Sample Kernel Independence Test with Application to Microbiome Association Studies”