Kehui Chen

Kehui Chen is a Professor and Director of Graduate Studies in the Department of Statistics at the University of Pittsburgh, affiliated with the Dietrich School of Arts and Sciences. She holds a PhD from the University of California, Davis (2012) and a BS from Peking University (2007). Her research focuses on functional data analysis, network modeling, and their applications in mental health, including schizophrenia and suicide risk prediction. She develops methods for covariance structure modeling, nonparametric prediction, and community detection in multi-layer networks.

Her work bridges statistical theory and practical applications in neuroscience, with notable contributions to longitudinal studies in midlife women's health and brain connectivity analysis. She has published extensively in top journals like Biometrika and JASA. Current research trends emphasize weak separability tests for multi-way data and adaptive stochastic block models incorporating node features.