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
Tsvetshop
Tsvetshop researchers aim to develop practical solutions to natural language processing problems that combine sophisticated learning and modeling methods with insights into human languages and the people who speak them.
UbiComp Lab
The Ubiquitous Computing (UbiComp) Lab develops innovative systems for health sensing, low-power sensing, energy sensing, activity recognition and novel user interface technology for real-world applications.
Faculty Members
Centers & Initiatives
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.
Change is a cross-campus collaboration that explores the challenges of developing technology in the context of positive social change. It seeks to make connections between researchers, outside organizations, and the public to inspire the development of new capabilities aligned with the interests of those most in need.
Highlights
Allen School News
The Institute of Electrical and Electronics Engineers (IEEE) recognized Kemelmacher-Shlizerman for her “contributions to face, body, and clothing modeling from large image collections,” including pioneering virtual try-on tools and bringing the technology to the mainstream.
Allen School News
The team co-led by professor emeritus Richard Ladner examined how people with visual and motor disabilities select, adapt and use mobile devices in their everyday lives. Since its publication in 2009, the findings have helped guide new innovations in mobile device accessibility.
WIRED
Professor Shyam Gollakota spoke to WIRED about his work with UW spinout Hearvana leveraging AI to enable people to go beyond noise canceling to customize their soundscape — including selectively amplifying sounds or voices they want to hear while minimizing ones they don’t.