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
Personal Robotics Lab
Our mission is to develop the fundamental building blocks of perception, manipulation, learning, and human-robot interaction to enable robots to perform complex physical manipulation tasks under clutter and uncertainty with and around people.
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
Associate Teaching Professor
Teaching Professor
Professor
Professor
Centers & Initiatives
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.
The Community-Engaged Computing Initiative (CECI) is a joint initiative to support community-centered scholarship and research within the broad computing and information field. Co-led by the Paul G. Allen School of Computer Science & Engineering, the Department of Human Centered Design & Engineering, and the Information School, the initiative was launched in 2025 through a gift from Google. CECI supports projects that bring UW faculty and graduate students together with community partners to bring sustainable, equitable, and inclusive technology into real-world contexts.
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.