Education:
PhD, Statistics, Northwestern University, 2014.
Bio:
Fengqing (Zoe) Zhang, PhD, is an associate professor in the Department of Psychological and Brain Sciences. Prior to joining 91制片厂, she obtained her PhD degree in Statistics at Northwestern University. Her research interests primarily center on the development of multimodal integrative approaches and advanced statistical methods to improve our understanding of health and aging. Specifically, her lab focuses on modeling complex, high-dimensional data, such as neuroimaging (e.g., MRI, DTI, fMRI, PET) and rich behavioral datasets, to investigate brain development and aging, neurodegenerative diseases (e.g., Alzheimer鈥檚 disease), and psychiatric disorders. Her methodological approaches include machine learning, Bayesian inference, and high dimensional data analysis. She also specializes in the design and statistical analysis of clinical trials, particularly focusing on sample size optimization, adaptive designs, and enrichment strategies. In addition, she works on statistical methods development to inform real-time, individualized treatment sequences (e.g., Just-in-Time Adaptive Interventions) and to integrate multimodal data from wearable devices (e.g., fitness trackers, heart rate monitors).
Impact:
Zhang鈥檚 work in quantitative modeling is driven by the goal of enhancing our understanding of complex and high-dimensional data and, ultimately our ability to fully utilize the informational complexity for new levels of scientific discovery.
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. Zhang and her team are committed to making a difference in the statistical thinking and computational approaches required to handle these challenges.