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Interaction with the Physical World

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

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.

Professor Dieter Fox and a student demonstrate a remote operated robotic arm attempting to pick up a block

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

Professor

Associate Teaching Professor

Assistant Professor


Centers & Initiatives

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.

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.

Highlights


Allen School News

Itani, who works with Allen School professor Shyam Gollakota in the Mobile Intelligence Lab, was recognized for exceptional early-career research advancing AI systems for “superhuman” hearing.

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.