My research focuses on coarse-graining non-equilibrium many-body dynamics with generative machine learning.

I am interested in methods that:

• preserve the important structure of the underlying dynamics
• provide interpretable approximations rather than black-box predictions
• generalize across diverse physical systems and regimes

In practice, that means I spend my time thinking about reduced representations, generative models for physical systems, and ways to make complex dynamical data more accessible.

• coarse-graining strategies for non-equilibrium systems
• generative models for physical dynamics
• scientific machine learning methods
• numerical experimentation and analysis
• software development