Allen School researchers are at the forefront of exciting developments in AI spanning machine learning, computer vision, natural language processing, robotics and more.
We cultivate a deeper understanding of the science and potential impact of rapidly evolving technologies, such as large language models and generative AI, while developing practical tools for their ethical and responsible application in a variety of domains — from biomedical research and disaster response, to autonomous vehicles and urban planning.
Groups & Labs
Graphics & Imaging Lab (GRAIL)
The work of the Graphics & Imaging Laboratory spans computer graphics, computer vision, generative AI, computational photography, virtual reality, animation and games.
SAMPL
SAMPL is an interdisciplinary machine learning research group exploring problems across the system stack, including deep learning frameworks, specialized hardware for training and inference, new intermediate representations and more.
Faculty Members
Centers & Initiatives
The Tech Policy Lab is a unique, interdisciplinary collaboration at the University of Washington that aims to enhance technology policy through research, education, and thought leadership. Founded in 2013 by faculty from the Paul G. Allen School of Computer Science & Engineering, Information School, and School of Law, the Lab aims to bridge the gap between technologists and policymakers and to help generate wiser, more inclusive tech policy.
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
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.
UW News
AI trained on data from the entire internet won’t work equally well for people in different cultures. But when UW researchers fed AI agents data from a kitchen simulation game, they found that the AI absorbed cultural values from observing human behavior — similar to what children do.
UW News
The prototype from researchers in the Mobile Systems Lab led by Allen School professor Shyam Gollakota detects the cadence of a conversation and automatically tracks participants’ voices for the wearer while muting the rest.