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Artificial Intelligence

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

RAIVN Reserch Lab image featuring a raven wearing dark sunglasses

RAIVN Lab

The Reasoning, AI, and VisioN (RAIVN) Lab directed by Prof. Ali Farhadi and Prof. Ranjay Krishna focuses at the intersection of computer vision, machine learning, natural language processing and robotics and is targeted towards helping computers…

Robotic arm feeding seated person a strawberry on a fork with an inset image of the robot mapping features of their face

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.


Faculty Members

Faculty


Centers & Initiatives

The interdisciplinary DUB group at the University of Washington advances research, collaboration and teaching related to the interaction between design, people, and technology.

RAISE envisions a future where AI systems are developed and used in alignment with human ethics and values. With researchers from over a dozen labs across disciplines, RAISE is a leading center for research and education: building, evaluating, and envisioning AI technologies in the area of Responsible AI.

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.