Members
Farnoosh Babazadeh
Ph.D. student
Farnoosh Babazadeh’s research interests include empirical Bayes methods to estimate the local false discovery rate with applications to analyzing genomics data.
Postdoctoral fellow
Volunteer visiting student researcher
Corey Yanofsky, PhD
Volunteer researcher
Corey Yanofsky’s research focuses on the application of Bayesian, empirical Bayes, and likelihood methods to large scale data sets in microarray studies, proteomics, lipidomics, and genome-wide association analyses.
David R. Bickel, PhD
Associate Professor
As the PI of the Statomics Lab, David Bickel develops statistical and computational methods for the analysis and interpretation of genomic information, including SNP data from genome-wide association studies and microarray gene expression measurements. Research and software
Ye Yang, PhD
Former postdoctoral fellow
Ye Yang’s research interests include Bayesian analysis and Markov chain Monte Carlo (MCMC) methods, analyses of linear and non-linear mixed models with variance heterogeneity, variable selection methods, mixture models, multiple statistical testing issues, and analyses of high-dimensional genomic data.
Tasneem Zaihra, PhD
Former postdoctoral fellow
Tasneem Zaihra’s area of interest is analysis of overdispersed proportions and counts.
In the case of over dispersed proportions, she works on interval estimation of epidemiological indices such as risk difference, risk ratio, relative risks etc, that are often used to report clinical findings and play an important role in epidemiological investigations.
In the case of over dispersed counts, that arise in diverse fields, including biostatistics, radioimmunoassay, pharmacokinetics modeling, enzyme kinetics, quality control etc, her study involves variance function estimation for semi-parametric analysis of count data.
She spent a summer collaborating with the Bickel lab in research on bootstrap estimation of confidence intervals for microarray data.
Zahra Montazeri, PhD
Former postdoctoral fellow
Zahra Montazeri’s research involved (a) statistical methods in classification and discriminant analysis with particular attention to: classification with missing covariates (complex data), (b) missing data and imputation, with particular applications to nonparametric curve estimation (regression and density curves), (c) computer-intensive inference, in particular bootstrap methods.
Zhengmin Zhang, PhD
Former postdoctoral fellow
Zhengmin Zhang’s Ph.D thesis research focused on estimation in mixture models, in particular (a) the identifiability of the model, (b) the geometric method in maximum likelihood estimation and (c) the method of moments in the construction of consistent estimates of mixing distributions. Her current research focuses on methods of estimation for large-scale-statistics. Her other interests are in the theory of characteristic functions, information theory and limit theory.
Yui Zhu
Former volunteer programmer
Pei-Chun Hsieh, BSc
Former visiting student researcher
Pei-Chun Hsieh’s research involves (a) microarray data preprocessing using the R language, (b) statistical prediction of regulating genes in yeast and bacteria, and (c) hypothesizing yeast and bacteria gene networks from the model predictions.
Group pictures
The Statomicists in 2011
The Statomicists in 2010
The Statomicists in 2008
