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Faculty/Staff Directory

Carlos Carvalho

Carlos Carvalho
CBA 6.472 (512-471-5823)

Professor of Statistics

Information, Risk, and Operations Mgmt.


Carlos M. Carvalho is an associate professor of statistics at McCombs. Dr. Carvalho received his Ph.D. in Statistics from Duke University in 2006. His research focuses on Bayesian statistics in complex, high-dimensional problems with applications ranging from finance to genetics. Some of his current projects include work on large-scale factor models, graphical models, Bayesian model selection, particle filtering and stochastic volatility models. Before moving to Texas Dr. Carvalho was part of the faculty at The University of Chicago Booth School of Business and, in 2009, he was awarded The Donald D. Harrington Fellowship by The University of Texas, Austin. Dr. Carvalho is from Rio de Janeiro, Brazil and before coming to the U.S. he received his Bachelor degree in Economics from IBMEC Business School (Rio de Janeiro) followed by a Masters degree in Statistics from the Federal University of Rio de Janeiro (UFRJ).


H. Lopes and Carlos Carvalho. Online Bayesian Learning in Dynamic Models. Hierarchical Models and MCMC, forthcoming.
P. Richard Hahn and Carlos Carvalho. 2015. Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective. Journal of the American Statistical Association 110(509), 435-448.
Richard P. Hahn, Carlos Carvalho, and Sayan Mukherjee. 2013. Partial Factor Modeling: Predictor-Dependent Shrinkage for Linear Regression. Journal of the American Statistical Association 108(503), 999-1008.
P. Hahn, Carlos Carvalho, and James Scott. 2012. A Sparse Factor Analytic Probit Model for Congressional Voting Patterns. Journal of the Royal Statistical Society: Series C (Applied Statistics) 61(4), 619-635.
H. Wang, C. Reeson, and Carlos Carvalho. 2011. Dynamic Financial Index Models: Modeling Conditional Dependencies via Graphs. Bayesian Analysis 6.
Carlos Carvalho, H. Lopes, and O. Aguilar. 2011. Dynamic Stock Selection Strategies: a Structure Factor Model Framework. Bayesian Statistics 9.
H. Lopes, Carlos Carvalho, M. Johannes, and N. Polson. 2011. Particle Learning for Sequential Bayesian Computation. Bayesian Statistics 9.
Jose M. Quintana, Carlos Carvalho, and James Scott. 2010. Bayesian Forecasting, Futures Markets, and Risk Modelling, in Handbook of Applied Bayesian Analysis, Anthony O'Hagan and Mike West, eds. Oxford University Press.
J. M. Quintana, Carlos Carvalho, and J. Scott. 2010. Futures Markets, Bayesian Forecasting and Risk Modeling, in The Handbook of Applied Bayesian Analysis,
J. Lucas, Carlos Carvalho, D. Merl, and M. West. 2010. In-Vitro to In-Vivo Factor Profiling in Expression Genomics, in Bayesian Modeling in Bioinformatics,
Carlos Carvalho, M. Johannes, H. F. Lopes, and N. G. Polson. 2010. Particle Learning and Smoothing. Statistical Science 25(1), 88-106.
Carlos Carvalho, H. Lopes, N. Polson, and N. Taddy. 2010. Particle Learning for General Mixtures. Bayesian Analysis 5.
H. Wang and Carlos Carvalho. 2010. Simulation of Hyper-Inverse Wishart Distributions in Non-Decomposable Graphs. Electronic Journal of Statistics 4.
Carlos Carvalho, N.G. Polson, and James Scott. 2010. The Horsehoe Estimator for Sparse Signals. Biometrika 97, 465-480.
Carlos Carvalho and J. Rickershauser. 2010. Volatility in Prediction Markets: A Measure of Information Flow in Political Campaigns, in The Handbook of Applied Bayesian Analysis,
J. Lucas, Carlos Carvalho, and M. West. 2009. A Bayesian Analysis Strategy for Cross-study Translation of Gene Expression Biomarkers. Statistical Applications in Genetics and Molecular Biology 8(1).
J. Chang, Carlos Carvalho, S. Mori, A. Bild, M. Gatza, Q. Wang, J. Lucas, A. Potti, P. Febbo, M. West, and J. Nevins. 2009. A Genomic Strategy to Elucidate Modules of Oncogenic Pathway Signaling Networks. Molecular Cell 34, 104-114.
J. Lucas, Carlos Carvalho, J. Chen, J. Chi, and M. West. 2009. Cross-study Projections of Genomic Biomarkers: An Evaluation in Cancer Genomics. PLoS One 4(2).
Carlos Carvalho, N. G. Polson, and James Scott. 2009. Handling Sparsity via the Horseshoe. Journal of Machine Learning Research W&CP 5, 73-80.
Carlos Carvalho and James Scott. 2009. Objective Bayesian Model Selection in Gaussian Graphical Models. Biometrika 96(3), 497-512.
James Scott and Carlos Carvalho. 2008. Feature-Inclusion Stochastic Search for Gaussian Graphical Models. Journal of Computational and Graphical Statistics 17(4), 790-808.
B. Rajaratnam, H. Massam, and Carlos Carvalho. 2008. Flexible Covariance Estimation in Graphical Gaussian Models. Annals of Statistics 36(6), 2818-2849.
Carlos Carvalho, J. Chang, J. Lucas, Q. Wang, J. R. Nevins, and M. West. 2008. High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics. Journal of the American Statistical Association 103, 1438-1456.
Carlos Carvalho and M. West. 2007. Dynamic Matrix-Variate Graphical Models. Bayesian Analysis 2, 69-98.
Carlos Carvalho and M. West. 2007. Dynamic Matrix-Variate Graphical Models. Bayesian Statistics 8, 585-590.
H. F. Lopes and Carlos Carvalho. 2007. Factor Stochastic Volatility with Time-varying Loadings and Markov Switching Regimes. Journal of Statistical Planning and Inference 137, 3082-3091.
Carlos Carvalho, H. Massam, and M. West. 2007. Simulation of Hyper-Inverse Wishart Distributions in Graphical Models. Biometrika 94, 647-659.
Carlos Carvalho and H. F. Lopes. 2007. Simulation-based Sequential Analysis of Markov Switching Stochastic Volatility Models. Computational Statistics and Data Analysis 51, 4526-4542.
J. Lucas, Carlos Carvalho, Q. Wang, A. Bild, J. R. Nevins, and M. West. 2006. Sparse Statistical Modeling in Gene Expression Genomics. Bayesian Inference for Gene Expression and Proteomics.
B. Jones, Carlos Carvalho, A. Dobra, C. Hans, C. Carter, and M. West. 2005. Experiments in Stochastic Computation for High-dimensional Graphical Models. Statistical Science 20, 388-400.

Professional Awards

Donald D. Harrington Faculty Fellow, The University of Texas at Austin2009
IBM Corporation Scholar, The University of Chicago2008
Dennis V. Lindley Prize - Honorable Mention2007
Leonard J. Savage Award for outstanding doctoral dissertation - Honorable Mention2006