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Welcome to the
Quantitative Psychology and Statistics Lab!
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As we
enter the era of Big Data,
characterized by the rapid growth of
data generation, there is immense
potential to gain new insights into
human behavior, health, and aging. Though
promises are held, the increasing amount
of data, the different types of data
from heterogeneous sources, and required
fast speed of data processing pose great
challenges to data management and
analysis. Many traditional methods that
perform well for moderate sample size or
low dimensional data do not scale to
massive data or high dimensional data.
Therefore, new
statistical thinking and
computational approaches are
required to handle these
challenges.
Our lab focuses on the development and
application of advanced statistical
models to analyze complex and high
dimensional data (e.g. neuroimaging
data, complex behavioral data). In
particular, we have been focused on
using multimodal neuroimaging (e.g.,
MRI, DTI, fMRI, PET) to examine
neurodegenerative diseases (e.g.,
Alzheimer’s disease) and psychiatric
disorders (e.g., PTSD, eating
disorders). The modeling approach
we take includes machine learning,
Bayesian inference, and high dimensional
data analysis. In addition, our group
works on the statistical methods
development for informing real time
individualized sequences of treatments
(Just-in-Time Adaptive Interventions)
and integrating multimodal data
generated from wearable devices (e.g.,
fitness trackers, heart rate monitors)
in the context of weight loss
maintenance and eating disorders.
Please visit our research page
for more information about our work.
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Prospective
Students
Our lab has funded
phd student
position available. Prospective
students who are interested in joining our
research group should contact Dr. Zhang
(fengqing.zhang@drexel.edu).
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