Advances in low- and no-power sensing, communication and interaction technologies offer new possibilities for blending digital innovation with our physical environment.
From gesture recognition that allows people to interact with objects in new ways, to low-power sensors that collect and transmit data about temperature, air quality, urban accessibility and more, our researchers are tapping into the potential of computation to transform how we experience the world around us.
Research Groups & Labs
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.
Robotics and State Estimation Lab
We are interested in the development of computing systems that interact with the physical world in an intelligent way. To investigate such systems, we focus on problems in robotics and activity recognition.
Allen School Faculty
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Centers & Initiatives
TCAT harnesses the power of open-source technology to develop, translate, and deploy accessible technologies, and then sustain them in the hands of communities. Housed by the Paul G. Allen School for Computer Science & Engineering, TCAT centers the experience of people with disabilities as a lens for improving design & engineering, through participatory design practices, tooling and capacity building.
DFab is a network of researchers, educators, industry partners, and community members advancing the field of digital fabrication at UW and in the greater Seattle region.
Highlights
HearingTracker
A technology known as semantic hearing developed in Allen School professor Shyam Gollakota’s lab could let users create acoustic bubbles, isolate chosen voices, and control individual sounds in their environment.
Fast Company
Allen School professor Jon Froehlich talks about how Project Sidewalk empowers communities by crowdsourcing data on pedestrian infrastructure, from curb ramps to broken pavement, to improve accessibility.
UW News
A team led by Allen School professor Vikram Iyer and Ph.D. student Zhihan Zhang published a paper in Nature Electronics describing a system that can assemble life cycle assessments, or LCAs, for electronic devices in about a minute with the help of AI agents.