Christopher Sims

Chris R. Sims is a faculty member in the Department of Cognitive Science at Rensselaer Polytechnic Institute, where he directs the Adaptive Computational Cognition (AdaCog) Laboratory. He received a B.S. in computer science from Cornell University in 2003 and a Ph.D. in cognitive science from Rensselaer in 2009. He was then a postdoctoral researcher at the University of Rochester and a faculty member at Drexel University, before returning to Rensselaer in 2017.

Sims's research seeks to identify the computational principles that underlie human intelligence, drawing on cognitive science, machine learning, and artificial intelligence. A central theme is the application of information theory to human cognition: the idea that the mind makes the best use of a limited capacity to store and process information.

In a 2018 paper in Science, Sims showed that Shepard's "universal law of generalization" follows from the principle of efficient coding. The result suggests that perception is shaped to minimize the cost of perceptual errors under constraints on information processing. Related work applies rate–distortion theory to visual working memory, explaining how the brain trades memory precision against limited capacity. This work has implications for understanding perceptual expertise in domains such as medicine.

A second line of research combines reinforcement learning with information theory. It asks how people learn behaviors and representations that maximize reward while staying as simple as possible. This work, including a 2025 paper in Nature Communications, shows that efficient coding helps explain how people generalize what they learn to new situations. Current projects in the lab extend these ideas to decision making, skilled action, and expertise.