Zhonghua Liu
Assistant Professor, Biostatistics, Columbia University, New York, NY, USA
Columbia Data Science Institute
Affiliate Member of New York Genome Center
Causal genomics • Causal inference • Deep learning • AI for science
I develop statistical foundations for causal inference in high-dimensional biological systems, integrating theory, method, genomics, and AI to enable intervention-level understanding.
[Google Scholar] [Contact: zl2509@cumc.columbia.edu ]
News:
• 08/2026 – Postdoctoral researcher Dr. Kan Chen will join Weill Cornell Medicine as a tenure-track Assistant Professor in Biostatistics.
• 04/2026 – Our paper was published in Nature! Featured by Columbia Mailman and other scientific media.
• 04/2026 – NIH CSR Special Emphasis Panel reviewer (R15/R16)
• 06/2025 – Served as invited ad hoc reviewer, NIH Center for Scientific Review (CSR), Biodata Management and Analysis (BDMA) Study Section.
• 2025 – Research on AI for Science featured in Columbia Magazine and other scientific media.
• 06/2024 – NIH R01 awarded, 2024--2029.
Selected Highlights:
• Principal Investigator (sole), NIH R01, 2024-2029.
• Associate Editor: Biometrics; Statistics in Medicine; Journal of Statistical Planning and Inference.
• Publications in Nature, Nature Computational Science, Cancer Cell, Cell Genomcis, JASA, JRSS-B, Biometria, Biometrics, AOAS, ICML, NeurIPS, etc.
• NIH CSR Panel Reviewer
• Causal inference
• Non-standard inference
• Statistical genetics and causal genomics
• Deep learning theory and statistically grounded AI
• AI for Genomics
Selected Publications:
• Nature (2026)
EBV–host genetic interactions in cancer risk
→ Genome-wide causal genetic interaction framework
• Statistics in Medicine (2026) – Invited Tutorial
Mendelian randomization methods for causal inference: Estimands, identification and inference
→ Introduced the concept of “causal genomics”
• Nature Computational Science (2025)
Rare variant analysis with multiple phenotypes in large-scale whole-genome sequencing studies
→ Scalable computational framework for biobank-scale genomic analysis
• Cancer Cell (2025)
Immunosequencing for early cancer detection
→ Statistical analysis of TCR-seq data
•Cell Genomics (2024)
Mendelian randomization integrated with AlphaFold 3 for protein-level inference
→ Identifies causal protein biomarkers and links genetic missense variation to protein 3D structural alterations
• Journal of the American Statistical Association (2022)
Large-scale causal mediation testing under composite null hypotheses
→ Top 10 Most Cited Papers in JASA in 2023.
[Full publication list → Publications page]
Contact:
Department of Biostatistics, Columbia University
722 West 168th Street
New York, NY 10032, United States
Email: zl2509@cumc.columbia.edu