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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

Phone: 713-563-4285
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. Cassese A., Guindani M., Vannucci M. A Bayesian Integrative Model for Genetical Genomics with Spatially Informed Variable Selection. Cancer Informatics. In Press.
2. Zhang L, Guindani M, Vannucci M, Versace F. A Spatio-Temporal Nonparametric Bayesian Variable Selection Model of fMRI Data for Clustering Correlated Time Courses. Neuroimage. In Press. NIHMSID: NIHMS578292.
3. Zhang S., Migliaccio G.C., Zandbergen P.A., Guindani M. Empirical Assessment of Geographically-based Surface Interpolation Methods for Adjusting Construction Cost Estimates by Project Location. Journal of Construction Engineering and Management. In Press. NIHMSID: NIHMS579384.
4. Sun W, Reich B, Cai T, Guindani M, Schwartzman A. False Discovery Control in Large-Scale Spatial Multiple Testing. Journal of the Royal Statistical Society, Series B. In Press. NIHMSID: NIHMS549452.
5. Shao B, Guindani M., Boyd D.D. Fatal Accidents for Instrument-Rated Private Pilots. Aviation, Space and Environmental Medicine. In Press.
6. Nolte M.J., Wang Y., Deng M.J., Swinton P.G,. Wei C., Guindani M., Schwartz R.J., Behringer R.R. Functional analysis of limb transcriptional enhancers in the mouse. Evolution and Development. In Press.
7. Cassese A., Guindani M., Tadesse M., Vannucci M. and Falciani F. A Hierarchical Bayesian Model for Inference on Copy Number Variants and their Associations to Gene Expression Changes. Annals of Applied Statistics 8(1):148-175, 4/2014. NIHMSID: NIHMS558750.
8. Krishna SG, Rao BB, Thirumurthi S, Lee JH, Ramireddy S, Guindani M, Ross WA. Safety of endoscopic interventions in patients with thrombocytopenia. Gastrointest Endosc. e-Pub 4/2014. PMID: 24721520.
9. Fronczyk K., Guindani M., Vannucci M., Palange A. and Decuzzi P. A Bayesian hierarchical model for maximizing the vascular adhesion of nanoparticles. Computational Mechanics 53(3):539-547, 3/2014. NIHMSID: NIHMS558758.
10. Jung SY, Hursting S, Guindani M, Vitolins MZ, Paskett ED, Chang S. Bioavailable Insulin- Like Growth Factor-I Inversely Related to Weight Gainin Postmenopausal Women regardless of Exogenous Estrogen. Cancer Epidemiol Biomarkers Prev. e-Pub 1/2014. PMID: 24363252.
11. Guindani M., Sepulveda N., Paulino C.D.M. and Mueller P. A Bayesian Semiparametric model for the analysis of Sequence Counts Data. Journal of the Royal Statistical Society, Series C 63(3):385-404, 2014. NIHMSID: NIHMS502433.
12. Nardo L, Sandman DN, Virayavanich W, Zhang L, Souza RB, Steinbach L, Guindani M, Link TM. Bone Marrow Changes related to Disuse. Eur Radiol 23(12):3422-31, 12/2013. e-Pub 7/2013. NIHMSID: NIHMS502872 In process at NIHMS.
13. Stingo FC, Guindani M, Vannucci M, Calhoun VD. An Integrative Bayesian Modeling Approach to Imaging Genetics. J Am Stat Assoc 108(503):876-891, 9/2013. PMCID: PMC3843531.
14. Di Mascolo D, J Lyon C, Aryal S, Ramirez MR, Wang J, Candeloro P, Guindani M, Hsueh WA, Decuzzi P. Rosiglitazone-loaded nanospheres for modulating macrophage-specific inflammation in obesity. J Control Release 170(3):460-468, 9/2013. e-Pub 6/2013. NIHMSID: NIHMS579371.
15. Migliaccio G., Guindani M., D'Incognito M. and Zhang L.. Empirical Assessment of Spatial Prediction Methods for Location Cost-Adjustment Factors. Journal of Construction Engineering and Management 139(7):858–869, 11/2012. NIHMSID: NIHMS5799379.
16. Reich J. R., Eidsvik J., Guindani M., Nail A. and Schmidt A. A class of covariate-dependent spatiotemporal covariance functions for the analysis of daily ozone concentration. Annals of Applied Statistics 5(4):2425-2447, 2011. NIHMSID: NIHMS558754.
17. 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.
18. Petrone S., Guindani M. and 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.
19. Duan J. A., Guindani M. and Gelfand A. E.. Generalized Spatial Dirichlet Process Models. Biometrika 94(4):809-25, 12/2007.
20. Guindani M. and Gelfand A.E. 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.

Grant & Contract Support

Title: Efficacy and Safety of Beta-adrenoceptor Inverse Agonist, Nadolol in Mild Asthma
Funding Source: NIH/NIAID (Subcontract from Baylor College of Medicine)
Role: MDACC Principal Investigator
Principal Investigator: Nicola Hanania
Duration: 8/15/2011 - 7/31/2014
 
Title: Texas Center for Cancer Nanomedicine - Biomathematics Core (PC-1)
Funding Source: NIH/NCI (Subcontract from The University of Texas Health Science Center - Houston)
Role: Co-Investigator
Principal Investigator: Anil Sood
Duration: 9/1/2010 - 7/31/2015
 
Title: Enhancing cancer outreach for low-income adults with innovative smoking cessation
Funding Source: NIH/NCI
Role: Co-Investigator
Principal Investigator: Alexander Prokhorov
Duration: 4/12/2010 - 1/31/2015
 
Title: Body Image Functioning in Cancer Patients Undergoing Facial Reconstruction
Funding Source: American Cancer Society (ACS)
Role: Co-Investigator
Principal Investigator: Michelle C. Fingeret
Duration: 1/1/2010 - 12/31/2013
 
Title: Quantifying Appearance Changes Following Breast Reconstruction
Funding Source: American Cancer Society (ACS) (Subcontract from University of Texas - Austin)
Role: Co-Investigator
Principal Investigator: Michelle C. Fingeret
Duration: 7/1/2009 - 6/30/2014
 
Title: The University of Texas M.D. Anderson Cancer Center SPORE in Melanoma (PC-C)
Funding Source: NIH/NCI
Role: Co-Investigator
Principal Investigator: Elizabeth Grimm
Duration: 12/1/2001 - 8/31/2015
 
Title: Cancer Center Support Grant - Biostatistics Shared Resource (Biostatistics Resource Group)
Funding Source: NIH/NCI
Role: Statistician
Principal Investigator: Ronald DePinho
Duration: 9/4/1998 - 6/30/2018

Last updated: 4/11/2014