Course Meeting Times

Lectures: 1 session / week, 3 hours / session

Course Overview

This course instructs students on how to develop technologies that help people measure and communicate emotion, that respectfully read and that intelligently respond to emotion, and have internal mechanisms inspired by the useful roles emotions play. Topics vary from year to year, and may include the interaction of emotion with cognition and perception; the communication of human emotion via face, voice, physiology, and behavior; construction of computers, agents, and robots having skills of emotional intelligence; the role of emotion in decision-making and learning; and affective technologies for education, autism, health, and market research applications. Weekly reading, discussion, and a term project are required.

Sample Topics - Final topics will be selected with input from this year’s class:

  • Emotionally Intelligent Human Computer Interaction
  • Emotion and Perception, Decision-making, and Creativity
  • Emotion and Learning
  • Physiology of Emotion
  • Neuroscience Findings Related to Emotion
  • Affect Recognition by Machines (include wearable systems)
  • Communicating Frustration / Stress in Autism and in Customer Experience
  • Responding to User Emotion to Reduce User Frustration
  • Inducing Emotion
  • Robots / Agents that “have” Emotion
  • Emotion and Behavior
  • Expression of Emotion by Machines / Agents / Synthetic characters
  • Philosophical, Social, Ethical Implications of Affective Computing
  • Machine / Mobile Empathy and Emotional Support
  • Lie Detection and Stress Detection


MIT students were required to obtain permission of the instructor.


All students are expected to attend all classes and all project and proposal presentations.

Absence from class, especially on project and proposal presentation days, will significantly affect your learning experience and grade.


Classroom participation 20%
Weekly assignments (reading / response) 35%
Final project and presentation 45%

Course Info

Learning Resource Types

assignment Problem Sets
notes Lecture Notes
assignment Written Assignments