Professor Reitter's research interests lie in computational cognition. His field develops models of human cognition that describe how humans communicate and how they make decisions. These models explain some of the most fascinating human abilities: verbalizing and spreading information within a vast network of social contacts. Portions of the human cognitive system are uniquely suited to communication, and these abilities are crucial to the intelligence emerging from human communities. Yet, the mechanisms underlying language comprehension and production are still poorly understood. While recent studies paint a picture of how memory and contextualization help humans comprehend a dialogue partner's ideas and individual language, we do not know whether human memory has evolved to support team-work and social cognition. Reitter's work investigates the relationship between cognitive processes in the individual and network-level emerging effects within teams.
The mind as a computer: A core methodology is to model cognitive processes using computer simulations. These models clearly formulate scientific theory, predict decisions, reaction time and local brain activity. To drive and evaluate model development, Dr. Reitter focuses on web- and lab-based behavioral experimentation and big data.
Big-data cognitive science:Reitter uses "big data": existing datasets of communication, or new, crowd-sourced experimental behavioral data of networked participants. Often simple (but serious) games are used to elicit decision-making and communication. Models are based on tightly validated cognitive architectures.
Reitter co-directs the Applied Cognitive Science Lab.