Bin Huang

Bin Huang is a Professor in the Division of Biostatistics and Epidemiology at the University of Cincinnati, affiliated with multiple departments including Pediatrics, Environmental Health, and Mathematical Sciences. His work focuses on causal inference methodologies (PCATS) to improve adaptive treatment strategies for chronic conditions in children, emphasizing healthcare equity and evidence-based approaches.

• Education: BS (Shanghai Jiao Tong University, 1991), MS/PhD (University of Cincinnati, 1995/2000)
• Research: Bayesian causal inference, electronic health records analysis, comparative effectiveness research in pediatric rheumatology and cardiology

Research contributions include developing open-source Bayesian methods for time-varying treatments and validating biomarkers for lupus nephritis. Awards include Wiley’s Top Cited Article (2023) and ISI membership (2016).

• Labs: PCATS Lab
• Collaborations: Cincinnati Children’s Hospital, interdisciplinary teams in clinical research