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.

Dr. Sims's research seeks to identify the computational principles that underlie human intelligence. Much of this work spans cognitive science, machine learning, and artificial intelligence.

One of his notable contributions is the application of information theory to human cognition. In a 2018 study published in Science, Sims demonstrated that the "universal law of generalization" can be derived from principles of efficient coding. This finding suggests that human perception exists to maximize the utility of behavior while subject to information processing constraints.

Sims has also explored information-theoretic limitations in visual working memory. His research has provided computational insights into how the brain stores and recalls visual information, in particular the balance between memory precision and capacity constraints. This research has implications for understanding and improving visual expertise in domains such as medicine.

Another line of research has examined the intersection of computational reinforcement learning and information theory. This research seeks to understand how biological organisms learn behavioral policies or representations that maximize utility of behavior while minimizing information complexity.