Our work in human-centered computing explores and enhances the ways in which people and communities engage with and experience technology.
Our research considers the personal, educational, cultural, and ethical implications of innovation. Drawing upon techniques from human-computer interaction, learning sciences, sensing and more, we aim to maximize the potential benefits of technology while minimizing potential harms to individuals, groups and society.
Groups & Labs
Wildlab
The Wildlab explores how technology can be biased against people who are unlike those who created it — and to build systems that help designers, developers, and researchers better support the needs and perspectives of different people.
Human-Centered Robotics Lab
In the Human-Centered Robotics lab we aim to develop robotics that are useful and usable for future users of task-oriented robots.
Allen School Faculty
Assistant Teaching Professor
Assistant Teaching Professor
Professor
Associate Teaching Professor
Centers & Initiatives
The interdisciplinary DUB group at the University of Washington advances research, collaboration and teaching related to the interaction between design, people, and technology.
The eScience Institute empowers researchers and students in all fields to answer fundamental questions through the use of large, complex, and noisy data. As the hub of data-intensive discovery on campus, we lead a community of innovators in the techniques, technologies, and best practices of data science and the fields that depend on them.
Highlights
Allen School News
In their 2017 paper, Roesner and her co-authors were among the first to investigate end-user security and privacy perspectives on then-emerging smart home technologies and recommend ways to help users make more informed security decisions.
UW News
To help shed light over safety and security concerns with current AI systems, UW News spoke with researchers including professors Franziska Roesner and Noah A. Smith.
Allen School News
In the first installment of a new Q&A series exploring grand challenges in computing, Reinecke and Smith discuss how they and their colleagues aim to answer the question, “How do we design AI in a way that is transparent and equally beneficial to all?”