Facial expressions are one of the most powerful tools for human social communication. However, understanding facial expression communication is challenging due to their sheer number and complexity. Here, I present a program of work designed to address this challenge using a combination of social and cultural psychology, vision science, data-driven psychophysical methods, mathematical psychology, and 3D dynamic computer graphics. Across several studies, I will present work that precisely characterizes how facial expressions of emotion are signaled and decoded within and across cultures, and shows that cross-cultural emotion communication comprises four, not six, main categories. I will also highlight how this work has the potential to inform the design of socially and culturally intelligent robots.