About Me

I’m a postdoctoral researcher at Columbia University, exploring the intersection of artificial intelligence, astrophysics, and cosmology.

I build machine learning models that analyze a mix of observational and simulated data for inference and emulation. My research addresses a broad spectrum of problems, including cosmological galaxy clustering, galaxy formation, galaxy clusters, and dust attenuation. My research focuses on robust and reliable ML for science, using Bayesian statistics and explainable AI to build trust in complex models. I co-lead the Implicit Likelihood Inference group within the Learning the Universe collaboration.

My publications are on Google Scholar and my open-source projects are on GitHub. I’m always looking for new collaborators, so please feel free to send me an email!