About the Course

Modern computational methods like machine learning, optimization, and signal processing enable novel interactive technologies. This Human-Computer Interaction (HCI) course will introduce you to the basics of such computational methods and guide you in learning how to apply them to design interfaces and interaction methods.

This course omits some essential topics in HCI:

We do not discuss user-centered design for building technologies. We focus on computational methods to equip you with elements for developing technologies.
This course does not cover empirical methodologies in HCI. However, topics such as statistical methods may be applicable in empirical contexts.
The course excludes topics such as sensors, actuators, circuit design, and other hardware-related aspects of HCI.

There are some prerequisites:

Good programming skills. We use Python in this course, so being able to use the language would help.
Undergraduate-level knowledge in linear algebra, calculus, probability, and statistics.
(Recommended) Exposure to HCI research and user-centered design. Although the course will focus on technical aspects of HCI, having a basic understanding of general HCI concepts would help. If you are unfamiliar with such topics, see the lecture notes in the following page: IS211 Interaction Design and Prototyping).

Lectures

Please bring your laptop every week. Every lecture involves some hands-on programming activities.

Lecturer: Kotaro Hara ([email protected], 6828 9691, SCIS1 4047)
TA: TBD
Class Time: TBD
Class Location: