Course No.: EECS 598
Credit Hours: 3
Instructor: Emily Mower
Prerequisites: Students should have familiarity with probability theory and machine learning tools
Human-centered computing (HCC) is the science of decoding human behavior. HCC seeks to provide a computational account of aspects of human behavior ranging from interaction patterns to individual emotion expression using techniques drawn from both signal processing and machine learning. However, the complexity of this new domain necessitates alterations to the techniques common within the machine learning field and a fundamental understanding of the domains under analysis.
In this seminar course we will cover the development of and state-of-the-art systems in the human-centered computing field. Students will develop a critical understanding of HCC systems ranging from human state recognition and classification systems to human-in-the-loop systems to quantitative human behavior analysis systems. The course evaluation will include student presentations of published HCC work and a final HCC-based project.