Area of research
Statistics and Probability · Artificial Intelligence
Research interest
Research interests include Statistical Methods and Inference, Bayesian Methods and Mixture Models, Statistical Methods and Bayesian Inference, and Financial Risk and Volatility Modeling.
Bayesian regularization: From Tikhonov to horseshoe
Deep learning for spatio‐temporal modeling: Dynamic traffic flows and high frequency trading
Deep learning for short-term traffic flow prediction
Deep Learning: A Bayesian Perspective
Proximal Algorithms in Statistics and Machine Learning
Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables
Bayesian Instrumental Variables: Priors and Likelihoods
Tracking Epidemics With Google Flu Trends Data and a State-Space SEIR Model
Local Shrinkage Rules, Lévy Processes and Regularized Regression