Prof. Philip Reiss

Philip Tzvi Reiss earned his Ph.D. in Biostatistics from Columbia University in 2006. From then until 2015 he worked at New York University School of Medicine, where he was promoted to Associate Professor of Child and Adolescent Psychiatry in 2013. He made Aliyah in 2015 and is now a Professor in the University of Haifa Department of Statistics. His statistical methods research has been supported by the U.S. National Science Foundation, the U.S. National Institute of Mental Health, and the Israel Science Foundation.  

biostatistics, multivariate analysis, functional data analysis, statistical modeling in neuroimaging.

• Reiss PT, Ogden RT (2007).  Functional principal component regression and functional partial least squares.  Journal of the American Statistical Association 102:984-996.
• Reiss PT, Ogden RT (2009).  Smoothing parameter selection for a class of semiparametric linear models.Journal of the Royal Statistical Society, Series B 71:505-523.
• Reiss PT, Ogden RT (2010).  Functional generalized linear models with images as predictors. Biometrics66:61-69.
• Reiss PT, Stevens MHH, Shehzad Z, Petkova E, Milham MP (2010).  On distance-based permutation tests for between-group comparisons.  Biometrics 66:636-643.
• Reiss PT, Schwartzman A, Lu F, Huang L, Proal E (2012). Paradoxical results of adaptive false discovery rate procedures in neuroimaging studies. NeuroImage 63:1833-1840.
• Reiss PT, Huang L, Chen YH, Huo L, Tarpey T, Mennes M (2014). Massively parallel nonparametric regression, with an application to developmental brain mapping. Journal of Computational and Graphical Statistics 23(1):232-248.
• Reiss PT, Huo L, Zhao Y, Kelly C, Ogden RT (2015). Wavelet-domain regression and predictive inference in neuroimaging. Annals of Applied Statistics 9(2):1076-1101.
• Reiss PT, Goldsmith J, Shang HL, Ogden RT (2017). Methods for scalar-on-function regression.International Statistical Review, in press.
• Reiss PT, Miller DL, Wu PS, Hua WY (2017). Penalized nonparametric scalar-on-function regression via principal coordinates. Journal of Computational and Graphical Statistics, in press.
• Reiss PT, Huang L, Wu PS, Chen H, Colcombe S (2017). Pointwise influence matrices for functional-response regression. Biometrics, in press.