Gong Tang

Gong Tang is a Professor and Associate Director of the NRG Oncology Statistics and Data Management Center (SDMC) at the University of Pittsburgh. He is affiliated with the Biostatistics department and contributes to public health through methodological research in missing data analysis and causal inference. His work focuses on developing robust statistical methods to address biases arising from misspecified missing-data models, particularly in clinical trials and personalized medicine applications.

Education:

• BS, Mathematics - Beijing University (1991)
• MS, Mathematics - Beijing University (1994)
• MA, Mathematics - Johns Hopkins University (1996)
• PhD, Biostatistics - University of Michigan (2001)

Research Interests:

• Robust statistical methods for missing data without parametric model specification
• Causal inference via principal stratification and empirical estimation
• Nonparametric regression with order restrictions
• Clinical assay development for breast cancer (e.g., Oncotype DX®)
• Design and analysis of phase III breast cancer treatment trials

Publications & Contributions: His research spans missing data theory (2003), causal inference in clinical trials (2022), and pivotal studies that changed breast cancer treatment protocols through chemotherapy regimen comparisons (2013) and genomic recurrence prediction tools (2004, 2006). He developed the 21-gene Oncotype DX panel for node-negative breast cancer patients, which has become a model for personalized medicine.

Contact: Email: got1@pitt.edu