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

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.

A conceptual graphic showing a jumble of letters spread out around a more concentrated ball of letters

Tsvetshop

Tsvetshop researchers aim to develop practical solutions to natural language processing problems that combine sophisticated learning and modeling methods with insights into human languages and the people who speak them.


Faculty Members

Faculty

Faculty

Faculty


Centers & Initiatives

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.

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

A team of University of Washington and NVIDIA researchers developed FlashInfer, a versatile inference kernel library that can help make large language models faster and more adaptable, and received a Best Paper Award at MLSys 2025 for their work.

Allen School News

Sharma (Ph.D., ‘24) won the 2024 award from the Association for Computing Machinery for leveraging AI to make high-quality mental health support more accessible, and Min (Ph.D., ‘24) received an honorable mention for developing a new class of efficient and flexible language models.

Allen School News

Starting fall 2025, this new part-time evening program is designed to help working professionals across a range of industries to understand and leverage the latest artificial intelligence and machine learning techniques as part of their work.