My research is guided by a simple, yet theoretically impactful, principle: Some—but far from all—individuals agree with each other on judgments. Whereas most prior work to date has focused on shared variance, there is likely even more insight to be gleaned by studying idiosyncratic variance, and the interaction of both sources of variance. My program of research exists at the intersection of social perception, cognitive science, and computer vision. A major focus of my research examines when and why individuals agree or disagree on judgments. I have primarily examined this through testing how individuals extract and utilize information from faces, but the general approach and methods apply to all judgments and preferences.

To empirically examine sources of variance in judgment I leverage behavioral, vision, and computer science to inform the complex process of human judgment. My research utilizes methods and tools from computer vision, advanced modeling, and vision science. These methods and tools are tightly integrated into my main research focus on shared and idiosyncratic contributions to perception and judgment.