Area of research
Statistics and Probability · Artificial Intelligence
Research interest
Research interests include Gibbs sampling, Computer science, Bayesian probability, Econometrics, Coronavirus disease 2019 (COVID-19), and Mathematics.
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
The United States COVID-19 Forecast Hub dataset
Respiratory virus transmission dynamics determine timing of asthma exacerbation peaks: Evidence from a population-level model
Proximal Algorithms in Statistics and Machine Learning
Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables
Data augmentation for non-Gaussian regression models using variance-mean mixtures
Local Shrinkage Rules, Lévy Processes and Regularized Regression
A Sparse Factor Analytic Probit Model for Congressional Voting Patterns