I’ll be teaching a new grad-level course in AI for science this Fall 2024.

Tentative topics:

• Review of ML and deep learning basics
• Bayesian modeling
• Data assimilation
• Physics-informed neural networks
• Theory-guided machine learning
• Neural operators
• Surrogate modeling
• Discrepancy modeling
• Differentiable simulators
• Causal inference
• AI for scientific discovery
• Enabling scientific applications 1: Uncertainty quantification
• Enabling scientific applications 2: Explainable AI
• Enabling scientific applications 3: AI safety

Reach out via email if any questions.