I work in theoretical and data-driven cosmology. Currently, my interests revolve around the non-linear aspects of the late-time universe, including cosmic voids, higher-order statistics for weak lensing, and the thermal Sunyaev-Zel'dovich effect. I am also interested in the galaxy-halo connection and field-level methods.

Methods-wise, I have experience running and working with numerical simulations, including full-physics, N-body, and approximate surrogates. Much of my work involves machine learning, in particular baryon pasting and implicit likelihood-inference. I strive to elevate applications of machine learning in cosmology from unwieldy black boxes to interpretable models with limited, well-defined scope.