Faculty and Alumni Honored at 2019 JSM in Colorado

At this year’s Joint Statistical Meeting (JSM), the American Statistical Association announced a Biometrics Jounal paper for the 2019 Outstanding Statistical Application Award. The winning paper was authored by Assistant Professor Liangyuan Hu, PhD’16 (Alumni), Professor Joseph W. Hogan (Faculty), Adjunct Assistant Professor and Moi University Instructor Ann W. Mwangi, PhD’11 (Alumni and Adjunct Faculty member), and Abraham Siika (Moi University). The paper, entitled Modeling the Causal Effect of Treatment Initiation Time on Survival: Application to HIV/TB Co-infection" was chosen for this year’s Outstanding Statistical Application Award, an award that was established in 1986 to recognize the authors of papers that demonstrate an outstanding application of statistics in any substantive field.

The JSM is the largest statistical event in the world, involving over 6,500 attendees from 52 countries! There are more than 600 sessions involving invited, topic-specific, contributed and poster presentations. Brown University and the School of Public Health was very well represented this year by Brown’s Department of Biostatistics’ faculty, students and alumni. Below are is a sampling of presentations made by Brown Biostatisticians:

  • Lorin Crawford participated in the Fiber Bundles in Statistical Inference and Probability panel presenting “A Statistical Pipeline for Feature Selection and Association Mapping with 3D Shapes”
  • Yizhen Xu (PhD Candidate), Tao Liu (Faculty), Rami Kantor, and Joseph Hogan (Faculty)  participated in the Graphical Models and Causal Inference panel presenting “Bayesian Framework for Predictive and Causal Modeling Using BART”
  • Mingyang Shan (PhD Candidate), Kali Thomas and Roee Gutman (Faculty)  participated in the The Multiple Adaptations of Multiple Imputation panel presenting “Multiple Imputation Procedure for Record Linkage and Causal Inference to Estimate the Effects of Home Delivered Meals”
  • Gabriella Silva (PhD Candidate), Amal N. Trivedi and Roee Gutman (Faculty)  participated in the SPEED: Missing Data and Causal Inference Methods, Part 1 panel presenting “Developing and Evaluating Methods to Impute Race/ Ethnicity in an Incomplete Dataset”
  • Yi Cao (PhD Candidate), and Roee Gutman (Faculty)  participated in the SPEED: Missing Data and Causal Inference Methods, Part 1 panel presenting “Comparison of Missing Data Imputation Methods in Longitudinal Study of ADRD Patients”
  • Bing Li participated in the SPEED:Statistical Methods for GWAs, Genetics, Genomics, and Other Omics Studies, Part 1 panel presenting “Prediction with Microbiome Sequencing Data via MultiKernel Learning”
  • Samantha Morrison (PhD Candidate), Jon Steingrimsson (Faculty) and Constantine Gatsonis (Faculty) participated in the SPEED: Food, Environment, Biomedical Imaging and Physical System Visualization/Learning, Part 1 and SPEED: Food, Environment, Biomedical Imaging and Physical System Visualization/Learning, Part 2 panel presenting “Survival Analysis for Medical Imaging Data”
  • Jiabei Yang (PhD Candidate), Christopher Schmid (Faculty), and Jon Steingrimsson (Faculty) participated in the SPEED: Biostatistical Methods, Application, and Education, Part 1 and SPEED: Biostatistical Methods, Application, and Education, Part 2 panel presenting “Sample Size Calculations in Single-Case Designs”
  • Christopher Schmid (Faculty) participated in the Modern Statistical Methods for Comparative Effectiveness Research panel presenting “Incorporating Information from a Network of Personalized Trials to Facilitate Individualized Treatment Choice”
  • Anthony Scotina (Alumni) and Roee Gutman (Faculty) participated in Novel Methods for Causal Inference in Health Policy panel presenting “Matching Algorithms for Causal Inference with Multiple Treatments”
  • Roee Gutman (Faculty), Anthony Scotina (Alumni), Robert J Smith, and Andrew Zullo participated in Recent Advances in Propensity Score Methods for Observational Studies with Multiple Treatments presenting “Approximate Bayesian Bootstrap Procedures to Estimate Multilevel Treatment in Observational Studies with Application to Type 2 Diabetes Treatment Regimens”
  • Hong Li (Alumni) and Constantine Gatsonis (Faculty) participated in the Biomarker Evaluation and Winning Student Papers on Medical Devices and Diagnostics panel presenting “Combining Biomarker Trajectories to Improve Diagnostic Accuracy in Prospective Cohort Studies with Verification Bias”
  • Xiaotian Wu (PhD Candidate) and Zhijin Wu (Faculty) participated in Contributed Poster Presentations: Section on Statistics in Genomics and Genetics presenting “Sparse Probabilistic NMF for Single Cell RNA Sequencing”
  • Jon Steingrimsson (Faculty), Samantha Morrison (PhD Candidate) and Constantine Gatsonis (Faculty) participated in the Risk Prediction Methods and Applications in Risk Stratified Prevention session presenting “Using Deep Learning to Build Risk Prediction Models for Time-to-Event Outcomes”
  • Jun Ke (PhD Cadidate), Xuefei Cao and Xi Luo (Faculty) participated in the Brain Connectivity Studies session presenting “Spatial and Temporal Correlation Analysis with an Application to fMRI Data”
  • Zhijin Wu (Faculty) participated in the Statistical Challenges and New Developments in Genomics session presenting “Evaluation of Cell Clustering in Single Cell Data”
  • Michael Lopez (Alumni) participated in the SPEED: Statistics in Sports; Physical Activity/Sleep Studies, and Nonparametrics Part 2 session presenting “Meta-Analysis to Quantify Properties of Quarterback Metrics”