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Stanford University · Bio-X
Wong Lab
Statistical methods. Biological discovery.
Our research
We develop statistical and computational methods to advance computational biology and personalized medicine. Our research spans multivariate analysis, machine learning, causal inference, Monte Carlo methods, differential equations, and high-performance computing.
Explore our publications
Research directions
Current interests
Likelihood-free and simulation-based inference, generative modeling, and principled methods for learning from complex stochastic systems
Single cell genomics and gene regulatory analysis
Sequencing-based GWAS
Semiconductor-based automation of biological experiments
Research support
- National Science Foundation
- National Institutes of Health
- Department of Veterans Affairs