Describes the characteristics of interaction between humans and computers and demonstrates techniques for the evaluation of user-centered systems. Crosslisted with PSYC 6750.

Basic concepts and methods of artificial intelligence including both symbolic/conceptual and numerical/probabilistic techniques.

This course introduces students to individual, interpersonal, and societal influences on health, and how such factors influence health across populations and create disparities in health. Using this knowledge as a foundation, the course examines how digital health technologies can be designed to address wellbeing barriers that disproportionately and unfairly diminish the health of subpopulations, eliminate preventable gaps in health between populations, and help all individuals achieve their highest possible state of health. Furthermore, this course examines how varied influences on health shape access to, utilization of, and the impact of digital health systems. Students will learn how to apply theory, empirical insights, and perspectives from the social, behavioral, and public health sciences in the design and evaluation of digital health systems. Foundations of public health will be examined; additionally, the course will have a central focus on applying human-centered design concepts to the domain of digital health. 

"Introduction to graduate-level topics in operating systems using research papers, textbook excerpts, and projects. Provides students thorough comprehension of distributed and parallel computer systems. Credit is not awarded for both CS 4210 and CS 6210."

Special Topics

Courses of timely interest to the profession, conducted by resident or visiting faculty.

Topics focus on deep learning techniques for modeling and understanding human language and text data. The course requires strong mathematical and programming skills; in-person attendance and an in-class midterm exam. Students may not receive credit for both CS 4650 and CS 7650.

Multidisciplinary perspectives on cognitive science. Interdisciplinary approaches to issues in cognition, including memory, language, problem solving, learning, perception, and action. Crosslisted with PST, PSYC, and ISYE 3790.

Independent research conducted under the guidance of a faculty member.