Carlos M. Carvalho studies Bayesian statistics in complex, high-dimensional problems with applications ranging from finance to genetics. His current projects include research on large-scale factor models, graphical models, Bayesian model selection, particle filtering, and stochastic volatility models.
Carvalho's published work includes "High-dimensional Sparse Factor Modelling: Applications in Gene Expression Genomics," Journal of the American Statistical Association(2008); "Flexible Covariance Estimation in Graphical Gaussian Models," The Annals of Statistics (2008); "Simulation of Hyper-inverse Wishart Distributions in Graphical Models," Biometrika (2007); "Dynamic Matrix-Variate Graphical Models," Bayesian Analysis (2007); "Simulation-based Sequential Analysis of Markov Switching Stochastic Volatility Models," Computational Statistics and Data Analysis (2007) and "Experiments in Stochastic Computation for High-dimensional Graphical Models," Statistical Science (2005).
Carvalho earned a bachelor's degree in economics from IBMEC Business School in Rio de Janeiro in 1999. He earned a master's degree in statistics from the Federal University of Rio de Janeiro in 2002 and a master's degree and PhD in statistics from Duke University in 2006. Most recently, as a postdoctoral research associate at Duke University, he was involved in a variety of collaborative work in genomic projects through the Duke Integrated Cancer Biology Program.
2017 - 2018 Course Schedule