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Human-Centered Computing

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

Street scene overlaid with color-coded object recognition labels for depicted car, bicycle, vegetation, utility pole, and manhole cover

Makeability Lab

The Makeability Lab specializes in Human-Computer Interaction and applied machine learning for high-impact problems in accessibility, computational urban science, and augmented reality.

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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

Faculty

Faculty


Centers & Initiatives

The Institute for Medical Data Science (IMDS) is a joint effort among the Schools of Medicine and Public Health and the College of Engineering, including the Allen School to lead the development and implementation of cutting-edge AI and data science methods in medical data science. By harnessing the power of AI across diverse health determinants, IMDS aims to improve patient health, provider satisfaction, and healthcare operations, particularly in the Pacific Northwest region.

Globe.AI is a multidisciplinary community of researchers at the University of Washington who aim to create equitable, responsive AI technologies that can adapt to individuals from diverse cultures and communities, including to different norms, languages, behaviors, and communication styles.

Highlights


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.

Allen School News

The fellowship will support Zhang’s work in sustainable ubiquitous computing, including the development of recyclable electronics and leveraging artificial intelligence to estimate carbon footprints and provide personalized health insights.