Jon Freeman, Ph.D., is Associate Professor of Psychology at Columbia University and director of the Social Cognitive & Neural Sciences Lab. His research examines how people understand the social world through a coordination of visual, social, and affective processes. In particular, his work focuses on the cognitive and neural mechanisms underlying person perception, bias and stereotyping, and the real-time dynamics of social and emotional judgments, including the interplay between social cognition and visual perception. He takes an integrative and multi-level approach that makes use of techniques such as functional neuroimaging, computational modeling, and behavior. He has also advanced mouse-tracking methodology, developing tools that capture split-second decision dynamics through response-directed hand movement.
Freeman is the recipient of a number of awards, including the National Science Foundation CAREER Award, the Association for Psychological Science’s Janet T. Spence Award for Transformative Early Career Contributions, and early career awards from the Federation of Associations in Behavioral & Brain Sciences, the Social & Affective Neuroscience Society, the Society for Personality & Social Psychology, the International Social Cognition Network, and the Society for Social Neuroscience.
STEM Workforce and Data Equity Work
Freeman's work in this vein is focused on resolving the blind spots of policymakers and researchers in understanding and advancing the U.S. STEM workforce. Since 2018, he has been working to have sexual orientation and gender identity (SOGI) demographics incorporated into the government’s national data collection and reporting systems for the STEM workforce, which are used to understand the PhD- and college-educated populations, develop strategies to better engage the nation's scientific talent, and ensure equal opportunity. By expanding data infrastructures at the national level while maintaining rigorous privacy and confidentiality standards, this work seeks to create transformative change through data-driven solutions that can better enable the success of all people in STEM.