معرفی
Dr. Zhonghua Liu is an Assistant Professor of Biostatistics at Columbia University's Mailman School of Public Health. He holds affiliations with Columbia's Data Science Institute (DSI) across four research centers: Foundations of Data Science, Health Analytics, Computational Social Science, and Computing Systems for Data-Driven Science. He earned his Ph.D. in Biostatistics from Harvard University under the supervision of Professor Xihong Lin.
His research program focuses on developing and applying novel statistical methods for causal inference, machine/deep learning theory, and high-dimensional data. Core interests include:
- Causal mediation analysis for genomic and clinical data
- Semiparametric efficiency theory in model optimization
- Mendelian randomization for genetic epidemiology
- Survival analysis with high-dimensional biomarkers
- Deep learning integration with traditional biostatistical frameworks
Recent publications (2022-2025) demonstrate a strong methodological focus on causal inference in genomics and precision medicine. Key themes include: 1) Robust Mendelian randomization techniques for weak genetic instruments, 2) Machine learning-enhanced mediation analysis frameworks, and 3) Integration of multi-omics data for causal pathway discovery. Methodological innovations frequently target applications in Alzheimer's disease, cardiovascular epidemiology, and COVID-19 outcomes.
