2021 Georgia Statistics Day

Georgia Statistics Day Conference Series  ♦  Emory University

The Department of Biostatistics and Bioinformatics at the Rollins School of Public Health, Emory University welcomes you to the 2021 Georgia Statistics Day (GSD). 

GSD is a one-day local research event designed to promote interdisciplinary research among statistical researchers and data scientists within the state of Georgia and vicinity states. Attendees of GSD generally include faculty, postdocs, and students from academic institutions, researchers from Centers for Disease Control and Prevention (CDC), and practitioners from industry. The program of GSD covers a diverse range of topics related to statistical methods, applications, and practice.

Registration is now open!

Keynote Speaker

Dr. Peter Gilbert, University of Washington, COVID-19 Vaccine Efficacy Trials and "Immune Correlates of Protection" in the Moderna COVE Trial. Dr. Gilbert is a Professor of Biostatistics at the Fred Hutch and University of Washington Department of Biostatistics, focusing on the design and analysis of clinical trials of candidate vaccines for HIV, COVID-19 and other infectious diseases. He specializes in statistical methods and data analyses of these trials to understand how vaccine efficacy depends on immune responses to vaccination and on genetic features of infectious pathogens, so-called sieve analysis. He is PI of the Statistical Center for the NIAID HIV Vaccine Trials Network, and plays a similar role for US Government supported Coronavirus Prevention Network COVID vaccine efficacy trials.

Plenary session speakers:

• Robert Krafty, Emory University, Adaptive Spectral Analysis and Learning of Nonstationary Time Series
• Ping Ma, University of Georgia, Statistical Computing Meets Quantum Computing
• Nicoleta Serban, Georgia Tech, Computational Methods for Healthcare Access Modeling

Invited session speakers:

• Craig Borkowf, CDC, Notes from the Field: Teaching Non-Statisticians about Best Practices Regarding P-Values and Statistical Significance
• Santu Ghosh, Augusta University, Large-Scale Simultaneous Testing Using Kernel Density Estimation
• Linwei Hu, Wells Fargo, Fitting Interpretable Machine Learning Models with Main Effect and Low-Order Interactions Using Boosted Model-Based Trees
• Pengsheng Ji, University of Georgia, Statistics for Statisticians: Looking into the Past Through Citations
• Wenjing Liao, Georgia Tech, Exploiting Low-Dimensional Structures of Data Sets in Machine Learning with Deep Neural Networks
• Ruiyan Luo, Georgia State University, Modeling Spiky Functions with Derivatives of Smooth Functions in Function-on-Function Regression
• Christina Mehta, Emory University, Nested and Multipart Studies: Flaming Fiasco or Efficiently Economical?
• Mohamed Mubasher, Morehouse School of Medicine, How Social Vulnerability Predicted the Frequency and Intensity of COVID-19: A Case in Point Using Georgia County-Specific Data
• Razieh Nabi, Emory University, The Role of Causal Mediation Analysis in Personalized Decision Making
• Ben Risk, Emory University, A Missing Data Method for Deconfounding in Neuroimaging Studies
• Heather Strosnider, CDC, Modernizing CDC’s Data and IT Infrastructure to Accelerate the Adoption of Advanced Statistical Methods
• Shihao Yang, Georgia Tech, Big-Data Infectious Disease Estimation:  From Flu to COVID-19
• Yonggang Yao, SAS, Counterfactual Analysis of Cross-Sectional Data using Quantile Process Regression
• Ting Zhang, University of Georgia, High Quantile Regression for Tail Dependent Time Series

Organizing Committee

• Limin Peng, co-chair, Emory University
• Hao Wu, co-chair, Emory University
• Max Lau, Emory University
• Lance Waller, Emory University
• Azhar Nizam, Emory University