Chris Sims, PhD
Department of Psychology
Learning and decision-making under uncertainty; Visual memory and perceptual expertise; Sensorimotor control and motor learning; Computational models of cognition
Chris Sims received a BS degree in computer science from Cornell University. Following his undergraduate studies, he enrolled in the cognitive science program at Rensselaer Polytechnic Institute, where he received his PhD in 2009. Chris held a post-doctoral research position at the University of Rochester before joining the faculty at Drexel University in 2013.
Sims' primary research interest lies in understanding how cognitive, perceptual, and motor resources are organized and coordinated towards the efficient achievement of goals in the world. Specific ongoing research projects include studying how the important features of a visual scene are selected and stored in short-term memory, and investigating how eye movements are coordinated with motor acts in natural tasks. Other research projects include examining how humans make decisions in situations characterized by limited information and uncertainty, and how (and how well) people learn from feedback in these environments. Each of these research questions are addressed using a combination of empirical studies and developing state-of-the-art computational models of cognitive processes. Computational cognitive models serve as an explicit implementation of a theory, but can also have practical applications, such as monitoring human performance in real-time to aid performance or detect errors, or assess the course and extent of learning.
My research uses experimental and computational modeling approaches to understand how humans learn, act, and make decisions in a world filled with uncertainty. In reaching for an object, the brain must compensate for time-delayed and uncertain sensory signals, and use this information to control a noisy and error-prone motor system. When we briefly look at a photograph, only a limited amount of information can be stored in working memory; as a result, the brain must be selective in what information is stored, and how it is encoded. These examples illustrate that both motor control and visual memory are low-level forms of decision-making under uncertainty. I am interested in studying how these low-level sensorimotor decisions are carried out, and how they relate to higher-level cognitive decisions under uncertainty. I am also interested in understanding how training, aging, and cognitive impairments influence our ability to adapt to the demands of a constantly-changing and uncertain world.