Skip to content

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

Stacked rocks in a beach scene

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.

Scatterplot of multi-colored dots, with a large cluster of dots occupying roughly two-thirds of the frame, with smaller clusters aligned by color and scattered individual dots arranged along one side of the main cluster

AIMS Lab

The AI for bioMedical Sciences (AIMS) Lab fundamentally advances the way AI is integrated with biology and clinical medicine by addressing novel scientific questions spanning explainable AI, model auditing, disease drivers, and more.


Faculty Members

Faculty

Faculty

Faculty


Centers & Initiatives

MEM-C is a NSF Materials Research Science and Engineering Center that integrates materials innovations with theory and computation to advance spin-photonic nanostructures and elastic layered quantum materials, aided by an “AI Core” that integrates artificial intelligence-driven materials discovery.

Change is a cross-campus collaboration that explores the challenges of developing technology in the context of positive social change. It seeks to make connections between researchers, outside organizations, and the public to inspire the development of new capabilities aligned with the interests of those most in need.

Highlights


WIRED

Professor Shyam Gollakota spoke to WIRED about his work with UW spinout Hearvana leveraging AI to enable people to go beyond noise canceling to customize their soundscape — including selectively amplifying sounds or voices they want to hear while minimizing ones they don’t.

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.