Computational cognitive modeling - Spring 2026
Instructor: Todd Gureckis and Mark Ho
Meeting time and location: TBD
Office hours: Default is in person, but email us to request zoom if need be.
Course numbers:
DS-GA 1016 (Data Science)
PSYCH-GA 3405.004 (Psychology)
Summary: This course surveys the leading computational frameworks for understanding human intelligence and cognition. Both psychologists and data scientists are working with increasingly large quantities of human behavioral data. Computational cognitive modeling aims to understand behavioral data and the mind and brain, more generally, by building computational models of the cognitive processes that produce the data. This course introduces the goals, philosophy, and technical concepts behind computational cognitive modeling.
The lectures cover artificial neural networks (deep learning), reinforcement learning, Bayesian modeling, model comparison and fitting, classification, probabilistic graphical models, and program induction. Modeling examples span a broad set of psychological abilities including learning, categorization, language, memory, decision-making, and reasoning. The homework assignments include examining and implementing the models surveyed in class. Students will leave the course with a richer understanding of how computational modeling advances cognitive science, how cognitive science can inform research in machine learning and AI, and how to fit and evaluate cognitive models to understand behavioral data.
Please note that this syllabus is not final and there may be further adjustments.
Pre-requisites
The course is designed for advanced students in psychology, data science, or computer science who are interested in understanding human and machine intelligence. Prerequisites are a basic familiarity with programming (we will use Python in the course problem sets) and comfort with talking about ideas from elementary calculus, linear algebra, and probability theory.
Grading
The final grade is based on the homeworks (65%) and the final project (35%).
Class participation may be used to decide grades in borderline cases.
Final Project
The final project will be done in groups of 3-4 students. A short paper will be turned in describing the project (max 6 pages). The project will represent either a substantial extension of one of the homeworks (e.g., exploring some new aspect of one of the assignments), implementing and extending an existing cognitive modeling paper, or a cognitive modeling project related to your research. We provide a list of project ideas here, but of course, you do not have to choose from this list.