Cognitive Science

The aim of the course is to present a unified view of cognitive science, based on a computational approach to analysing cognition. The course covers language, vision and attention, memory, motor control and action, and reasoning and generalization. All topics will be presented from a computational point of view. The course provides a basic grounding in the methods of cognitive science, focusing on computational modelling and experimental design. Suitable for all interested students.

On completion of this course, the student will be able to:

  • Demonstrate knowledge of key areas of cognitive science, and be able to take an integrated, rather than disciplinary perspective on the field.
  • Evaluate the most important conceptual problems in cognitive science and discuss the solutions that have been proposed.
  • Analyze and modify simple computational models in a variety of modeling paradigms.
  • Understand how cognition and cognitive science is societally situated and the ethical issues raised in researching cognition.


Fall + Spring

University of Edinburgh

Seminar in Cognitive Modelling

This course provides students an opportunity to explore their choice of topic in cognitive science in depth while honing their science communication skills and broadly surveying the foundations of cognitive science. The course aims to expose students to a variety of cognitive models (e.g., connectionist, Bayesian, quantum models) and to discuss and evaluate competing models for similar problems. Students will be expected to present and critique classic and recent research articles from the cognitive modelling literature, chosen from a list provided by the instructor.

On completion of this course, the student will be able to:

  • Demonstrate understanding of a range of classic and current articles in cognitive science/modelling by summarizing and critiquing their central ideas and/or results.
  • Demonstrate understanding of the relationship between computational models and cognitive theories, by being able to critically assess the theoretical adequacy of a given model.
  • Compare and contrast the strengths and weaknesses of different models of the same behaviour.
  • Search the literature and synthesize information from several papers on the same topic and create a coherent oral presentation on that topic.
  • Communicate (written and oral) key findings in cognitive science/modelling to inter-disciplinary audiences.

Previous Courses

University of Rochester

  • BCS 310: Senior Seminar. Fall 2016. Co-Instructor with Celeste Kidd.

Rochester Scholars Program

  • Building the Language Machine: An Introduction to Computational Linguistics. Summer 2016.
  • The Language Scientist: Linguist, Psychologist, Computer Scientist. Summer 2015.