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
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.
Robot Learning Lab
The Robot Learning Lab works on foundational research in machine learning, AI and robotics to develop intelligent robotic systems that can perceive, plan and act in complex environments and improve performance with experience.
Allen School Faculty
Assistant Professor
Professor
Professor
Professor
Centers & Initiatives
The Science Hub supports a broad set of programs — including fellowships for doctoral students, collaboration among researchers and support for collaborative research events — designed to accelerate artificial intelligence (AI), robotics and engineering in the Seattle area.
AI@UW aims to push the boundaries of AI technology in service to the public good by advancing ethical, interdisciplinary AI research while fostering practical innovation to benefit society at large.
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.