Course Offerings
Explore designing and implementing information technologies to improve healthcare delivery, healthcare management, and health outcomes. Offered on the letter-grade basis only.
Overview of public health and the information systems used to achieve public health goals. This course is divided into three parts: (1) overview of public health, (2) fundamentals of public health informatics, and (3) public health information systems.
Leveraging medical claims data to guide population health interventions, primarily through the use of machine learning models. The course will focus on the data processing pipeline, and no prerequisite knowledge of machine learning models is required
Explore principles and methodologies in health informatics research, including various approaches to data analysis, research design, and the application of informatics to health. Develop skills in reading, reviewing, and writing scientific publications, identifying research questions, initiating research, and communicating findings.
The course is designed for undergraduate students who are interested in understanding, analyzing, designing, evaluating, or developing technologies to serve the health needs of general consumers. It covers the concept of consumer health informatics, health behavior theories, health information seeking and information retrieval, various forms of consumer health systems, and the design and evaluation of such systems.
New Topic for Spring 2025. Description pending submission by instructor, Steve Hershman. Also offered as Informatics 320D.
Explore common data collection, management, and sharing practices in information technology and emerging technologies, such as search engines and AI systems. Students will read papers and engage in discussions about the pros and cons of established data practices and learn about the three main components of responsible data management: 1) consent and ownership, 2) privacy and anonymity, and 3) broader impact. Students will also practice how to collect data, make data-driven decisions, and design data-driven products through group projects as UX designers, researchers, and data scientists. The course will bring in interdisciplinary perspectives with guest speakers from archive science, engineering, and respponsible AI, to provide a holistic view of broader data ecosystems and infrastructures.
*THIS TOPIC WILL NO LONGER BE OFFERED AFTER SPRING 2025In this course, we will work to understand and address the challenges of misinformation, disinformation, and strategic manipulation in online environments. First, we will work to develop a deep understanding of the problem space. We will read and discuss existing research (both historical and contemporary) on how and why misinformation and disinformation spread. Next, we will explore the process, both personal and interpersonal, by which these issues can be approached and addressed in our own lives. This will involve reflecting on our own presuppositions, beliefs, and biases about information; and doing a project in which we apply the principles of Human-Centered Design to investigate different design directions for addressing misleading information. Students will gain important contextual knowledge and hands-on design experience that they can take into future professional domains (from education to policy to technology), where they can contribute to building more trustworthy information systems.
Introduction to combining human and machine intelligence to benefit people and society. Explore cutting-edge research on a number of subjects related to human-AI interaction, including the psychological and societal impacts of AI as well as design guidelines and methods for human-centered AI.