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Michele Guindani, Ph.D.

Present Title & Affiliation

Primary Appointment

Assistant Professor, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX

Research Interests

My current research interests include the use of a Bayesian (parametric and nonparametric) modeling framework for the analysis of problems in biostatistics, genetics, spatial statistics, and the solution of inverse problems (with particular regard to the PK/PD modeling). 

I am currently most interested in developing statistical models for data integration as well as Bayesian decision theoretical approaches to address the multiple comparison problems in hypotheses testing. 


For more information about my activities and research interests, please access my personal page.

Office Address

Email: mguindani@mdanderson.org

Education & Training

Degree-Granting Education

2005 Universita Commerciale Luigi Bocconi, Milano, Italy, PHD, Statistics
2001 Universita Commerciale Luigi Bocconi, Milano, Italy, MS, Cum Laude, Economics

Experience/Service

Academic Appointments

Assistant Professor, Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, 8/2007-8/2010
Postdoctoral Fellow, Department of Biostatistics, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, 8/2005-8/2007
Research Associate, Statistics and Decision Sciences, ISDS - Institute of Statistics and Decision Sciences, Duke University, Durham, NC, 6/2005-8/2005

Selected Publications

Peer-Reviewed Original Research Articles
1. Reich J R, Eidsvik J, Guindani M, Naild A, Schmidt A. A class of covariate-dependent spatiotemporal covariance functions for the analysis of daily ozone concentration. Annals of Applied Statistics, 2011.
2. Guindani M, Müller P, Zhang S. A Bayesian discovery procedure. J R Stat Soc Series B Stat Methodol 71(5):905-25, 11/1/2009. PMCID: PMC2914327.
3. Petrone S, Guindani M, Gelfand A E. Hybrid Dirichlet mixture models for functional data. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 71(4):755-82, 9/2009.
4. Duan J A, Guindani M, Gelfand A E. Generalized Spatial Dirichlet Process Models. Biometrika:809-25, 12/2007.
5. Guindani M, Gelfand AE. Smoothness Properties and Gradient Analysis Under Spatial Dirichlet Process Models. Methodology and Computing in Applied Probability 8(2):159-89, 2006.

Book Chapters
1. Gelfand AE, Guindani M, Petrone S. Bayesian nonparametric modelling for spatial data using Dirichlet processes (with discussion). In: Bayesian Statistics 8. Oxford University Press, 2007.
2. Guindani M, Do KA, Muller P, Morris J. Bayesian Mixture models for Gene Expression and Protein Profiles. In: Bayesian Inference for Gene Expression and Proteomics. Cambridge University Press, 2006.

Last updated: 3/8/2013