Chris Sims received a B.S. in computer science from Cornell University (2003), followed by a Ph.D. in Cognitive Science from Rensselaer Polytechnic Institute (2009). After completing his Ph.D., Dr. Sims held a postdoctoral research position at the University of Rochester, and a faculty position at Drexel University before joining the faculty at RPI in 2017.

Chris Sims has made significant contributions to our understanding of human cognition through his research in computational modeling. One of his notable contributions is the application of information theory to cognitive processes. In a 2018 study published in Science, Sims demonstrated that the "universal law of generalization"—which describes how organisms generalize experiences based on similarity—can be derived from principles of efficient coding. This finding suggests that human perceptual systems are optimized to maximize performance within the limits of their information-processing capacities.

Sims has also explored the information-theoretic limitations of visual working memory. Through ideal observer analysis, he has provided insights into how the brain stores and recalls visual information, highlighting the balance between memory precision and capacity constraints. This research has implications for understanding the efficiency of human memory systems and can inform the development of better training methods in fields that rely on visual expertise.

Additionally, Sims's interdisciplinary approach, combining cognitive science with machine learning techniques, has advanced our knowledge of how humans learn and make decisions under uncertainty. His work on reinforcement learning, visual memory, and sensory-motor control has broad applications, from improving educational strategies to enhancing artificial intelligence systems.