معرفی
Jincheng Shen is an Assistant Professor in the Department of Population Health Sciences at the University of Utah, with adjunct roles in the Departments of Family & Preventive Medicine and Internal Medicine. He completed his PhD in Biostatistics at the University of Michigan, Ann Arbor, postdoctoral training at Harvard T.H. Chan School of Public Health, and holds a BS and MS in Computer Science from Tsinghua University.
His methodological research focuses on causal inference, machine learning, high-dimensional data analysis, and statistical genetics. Applications span cancer studies, cardiovascular health, opioid use disorder, and chronic disease management. He actively collaborates with clinicians, biologists, and epidemiologists, particularly in analyzing longitudinal data from trials like SPRINT and AASK.
Recent publications (2024–2025) highlight his work in optimizing dynamic treatment regimes for diabetes, cardiovascular disease, and cancer, using machine learning and epigenetic biomarkers. He also contributes to school-based interventions for skin cancer prevention and community pharmacy protocols for opioid misuse.
Collaborations include large-scale studies on DNA methylation, aging, and environmental exposures, with applications in COPD, cardiovascular outcomes, and cancer risk prediction. His interdisciplinary approach bridges statistical methodology with real-world clinical and public health challenges.
