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        Quantitative Psychology and Statistics Lab


 
                                
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Welcome to the Quantitative Psychology and Statistics Lab!



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.




Prospective Students

My lab will be recruiting a fully funded PhD student for Fall 2027, with guaranteed funding support for five years. We are looking for motivated students interested in cognitive neuroscience, neuroimaging, and data science approaches to understanding brain and behavior. If our research aligns with your interests, I warmly encourage you to apply. Please feel free to reach out
(fengqing.zhang@drexel.edu) if you have any questions about the position, the program, or whether our lab might be a good fit for your research goals.