Jordan is an Assistant Professor at Stevens Institute of Technology. He is a cognitive scientist studying vision, learning, memory, and technology. Jordan's research includes the development of computational models of individual and group perception, learning, memory, and decision making, intending to apply these models to creating new technologies. He also develops tools to support behavioral and social science research.
When two people meet, they instantly size each other up, making snap judgments about everything from the other person’s age to their intelligence or trustworthiness based solely on the way they look. Those first impressions, though often inaccurate, can be extremely powerful, shaping our relationships and impacting everything from hiring decisions to criminal sentencing. Researchers […]
There’s a wide body of research that focuses on modeling the physical appearance of people’s faces. We’re bringing that together with human judgments and using machine learning to study people’s biased first impressions of one another. Given a photo of your face, we can use this algorithm to predict what people’s first impressions of you would be, and which stereotypes they would project onto you when they see your face. The algorithm doesn’t provide targeted feedback or explain why a given image evokes a particular judgment. But even so it can help us to understand how we’re seen — we could rank a series of photos according to which one makes you look most trustworthy, for instance, allowing you to make choices about how you present yourself.