I am an Assistant Professor of Psychology with a secondary appointment in the Department of Statistics and Data Science. My research aims to elucidate the biological computations underlying how we see, reason about, and interact with our physical environment. How does perception transform raw sensory signals arriving at our sensory organs into things like objects and people, into things that we can think about? This is the key question that drives our research, which we tackle primarily with computational modeling that brings together a diverse range of approaches including probabilistic modeling, simulation engines (including graphics and physics engines), and advanced approximate Bayesian inference (including deep neural networks, sequential importance samplers, approximate bayesian computation methods, and their hybrids). We test these models empirically in behavioral and neural experiments to give a unified account of neural function, cognitive processes, and behavior.