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Welcome to the
Quantitative Psychology and Statistics Lab!
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As data
can be produced and stored more
massively and cheaply from various
sources, we have
entered the era of Big Data. To
the extent that data can be analyzed, we
may be able to gain a completely new
perspective on our world, on how people
interact, spend their resources, and
organize their time. Though promises are
held, the high-dimensionality and huge
size of data sets can lead to
inferential problems of their
own—particularly spurious correlations,
noise accumulation, and incidental
homogeneity. 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).
Fall 2025
Our lab is
actively recruiting a
PhD student starting in Fall 2025.
Students who are interested in taking a
multi-modal approach (e.g., behavioral,
imaging, genetics, etc.) with large-scale
data (e.g., ABCD, UK Biobank, ADNI, etc.)
to examine brain development, health, and
aging are especially encouraged to apply.
Research projects can be tailored to best
suit applicant’s interests and future
goals. Please feel free to contact
Dr.
Zhang (fengqing.zhang@drexel.edu) for
further discussion.
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