Mojgan Golzy, PhD

Mojgan Golzy, PhD, is an associate research professor in the Department of Biomedical Informatics, Biostatistics, and Medical Epidemiology at the School of Medicine.Dr. Golzy’s work is driven by a passion for collaborative research and methodological innovation in response to compelling scientific challenges. Her primary research interests include cluster analysis, recurrent event data analysis and mixed-effects modeling. Notably, she has developed algorithms for clustering data on the surface of a sphere and introduced a nonlinear hierarchical mixed-effects model to better capture event-intensity rates. In addition to her statistical work, Dr. Golzy has explored topics in pure mathematics, including category theory and point-free topology.

A strong advocate for interdisciplinary collaboration, Dr. Golzy believes that working across disciplines is crucial for scientific progress. She has partnered with researchers from diverse fields, contributing both as a primary and co-author. Her collaborative studies have focused on addressing critical healthcare challenges, particularly in chronic kidney disease, bladder cancer and HIV. The statistical techniques used in her research include survival analysis, time-dependent Cox models, competing risks analysis, marginal structural modeling and propensity score matching. Through these efforts, Dr. Golzy aims to generate insights that not only deepen our understanding of complex health issues but also improve patient outcomes.