Class Schedule

Travis Seymour
  • Title
    • Associate Professor
  • Division Social Sciences Division
  • Department
    • Psychology Department
  • Affiliations Social Sciences Division
  • Phone
    831-459-3384, 831-600-5398, 831-459-5084
  • Email
  • Fax
    831-459-3519
  • Website
  • Office Location
    • Social Sciences 2, Room 357
  • Office Hours Friday 10-11:30am (Spring 2018)
  • Mail Stop Psychology Faculty Services
  • Faculty Areas of Expertise Cognitive Science, Computational Modeling, Psychology, Programming, Scientific Method
  • Courses Taught Psych 1: Introduction to Psychology; Psych 129: Human Learning and Memory; Psych 139D: Modeling Human Performance; Psych 138: Computer Programming for the Cognitive Sciences; Psych 20: Cognitive Processes; Psych 139N: Diversity in Cognitive Psychology; Psych 130B: Deception, Brain, and Behavior; Psych 252: Special Topics in Cognitive Psychology

Summary of Expertise

Role of working memory, consciousness, and executive control of the human performance of laboratory and applied tasks; cognitive processes amenable to strategic control and how they influence the way in which we maintain situational awareness; high levels of performance in complex and cognitive tasks; computational modeling of cognitive processes; human-computer/machine interaction; implications for use of technology in education

Research Interests

Travis Seymour's research involves theoretical and empirical investigations into the role of memory on human performance. The representation and access of perceptual memory, working memory and long-term memory constrain how and when we can use relevant information to complete many cognitive tasks. For example one line of work focuses on how working memory, situational awareness and executive control play a role in the multiple-task performance of automobile drivers and military jet pilots. A similar study focuses on how air-traffic controllers keep track of and remember critical visual-spatial information that dynamically changes over time.

In addition to these human-performance issues, Professor Seymour explores the role of conscious and unconscious executive processes in recognition memory. This project examines how constraints on memory access can allow us to detect the presence of privileged knowledge, despite explicit strategies to conceal this information. Because, under certain circumstances, we cannot control our response to information we recognize, results from this research have led to the formulation of a new mechanical "lie detector" potentially more accurate and reliable than previous candidates.

To test the various theoretical claims associated with each project, Professor Seymour employs the use of symbolic computational models constrained by robust a priori cognitive architectures such as the EPIC architecture (Meyer and Kieras, 1997a, 1997b). By comparing the results of these computer simulations to the data produced by human subjects, theories instantiated in the models can be verified in a precise and constrained manner.

For more information see Professor Seymour's lab website.

Biography, Education and Training

M.A., Ph.D., University of Michigan
B.A., Northwestern University

Selected Publications