Research

My research develops statistical foundations for AI-driven scientific discovery. I develop principled Bayesian and deep learning methods for reliable inference, interpretability, uncertainty quantification, and scalable computation, motivated by foundation models and large-scale scientific data. I also explore quantum computing for statistical inference and computation.

Current research directions include:

• Bayesian nonparametrics and deep learning
• scalable statistical computing and inference
• quantum statistical computing
• AI for scientific discovery, particularly in computational biology and protein science.