Most of my research is centered around the topic of Bayesian inference applied to physical problems. My interests:

1. Simulation-based inference
2. Probabilistic machine learning — diffusion, normalizing flows, VAEs, etc
3. Deep generative priors
4. Probabilistic volumetric rendering

I am also deeply interested in High-Performance Computing (HPC) and the general art of scaling up models/simulations.

In my previous life I was a researcher in the field of observational astrophysics (gravitational microlensing) and theoretical high energy astrophysics (plasma physics, physics of accretion, jets).