Kush is a candidate for
PhD in Biostatistics at the University of Illinois at Chicago.
He received his Masters degree in Electrical Engineering
from the University of Illinois at Chicago.
His research interests
include mixed-effect models especially for longitudinal
data, time-series analysis, missing data and the application
of statistics in the field of fMRI. Kush has been involved
in diverse statistical research projects in the health
sciences field under the guidance of Drs. Bhaumik and Gibbons.
The list of projects include testing problems of a gamma
random
variate, sample size determination for non-linear mixed
effects regression models, and estimation, modeling and
testing procedures for fMRI event related designs.
Kush
is also co-author of two software applications, fMRIviewer
and MIXZIP. fMRIviewer
allows the user to analyze fMRI event-related designs
using random-effects regression models. MIXZIP allows
the user
to estimate mixed-effects Zero-Inflated Poisson (ZIP)
regression models using the maximum marginal likelihood
approach. |
