At any given moment, our retinas receive millions of bits of information. This presents a monumental computational challenge to the visual system. Rather than process everything our sensory systems receive, we must rely upon heuristics to reduce computational load. My research centers around one such critical heuristic: ensemble perception, which refers to the idea that we can represent sets of objects using summary statistics. Instead of seeing every single leaf on a tree, we tend to see its overall ‘leafiness.’ It turns out that we engage this process even when we see crowds of faces. We perceive the average emotion of the crowd, but lose the individuals. Ensemble perception makes great intuitive sense — The visual system exploits the natural redundancy present in the world (e.g., most leaves are quite similar), which allows us to represent copious amounts of information in a succinct and elegant manner.
– Exploring the cognitive architecture of ensemble perception using individual differences
-Conceptual ensemble representations
-Prosthetic limb perceptual biases
-Capacity limitations of ensemble representations
-The role of motion in aesthetic preference