My work focuses on Bayesian statistics in complex, high-dimensional problems with applications ranging from finance to genomics. Here are some key aspects of my current research:

Use of complex state-space models in asset pricing problems;

Dimensionality reduction in large-scale multivariate problems;

Sparse models for high-dimensional covariance matrices, including graphical models and sparse factor models.

Model search/selection in linear models and graphical models;

Dynamic graphical models in multivariate financial time series and portfolio analysis;

Conditional variance models and multivariate stochastic volatility;

Sequential estimation and particle filtering;

Parallel statistical computation.