Dr. Guindani is a Professor in the Department of Biostatistics at the University of California, Los Angeles, USA. He received his Ph.D. degree in Statistics from Università Bocconi (Milan, Italy) in 2005. Prior to joining UCI in Fall 2016, Michele has held faculty positions in the Department of Mathematics & Statistics at the University of New Mexico (2007-2010) and in the Department of Biostatistics at the University of Texas MD Anderson Cancer Center (2010-2016).
Michele is a Fellow of the American Statistical Association (ASA), and he has served as Editor-in-Chief of the journal Bayesian Analysis (2019-2021).
For updated information, see his webpage: http://www.micheleguindani.info/
Research Interests:
- Analysis of High-Dimensional Data
- Neuroimaging Data
- Radiomics
- Integrative Genomics
- Microbiome
- Statistical Decision Making Under Uncertainty
- Multiple Comparison Problems
- Clustering
- Bayesian Modeling
- Bayesian Nonparametrics
- Doctor of Philosophy (PhD) in Statistics, Universita Bocconi, Italy
- Denti F, Guindani M, Leisen F, Lijoi A, Wasworth D, Vannucci M (2021) “Two-group Poisson-Dirichlet mixtures for Multiple Testing”, Biometrics, 77, 622-633.
- Warnick R., Guindani, M., Erhardt E., Allen E., Calhoun V., and Vannucci, M.. (2018) “A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data". Journal of the American Statistical Association, 151, 134-151
- W Sun, BJ Reich, TT Cai, M Guindani, A Schwartzman (2015) “False discovery control in large-scale spatial multiple testing.” Journal of the Royal Statistical Society. Series B, Statistical methodology
- S Petrone, M Guindani, AE Gelfand (2009) “Hybrid Dirichlet processes for functional data.” Journal of the Royal Statistical Society Series B
- JA Duan, M Guindani, AE Gelfand (2007) “Generalized spatial Dirichlet process models.” Biometrika 94 (4), 809-825