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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

A hand stacking square blocks in ascending heights like a graph

Interactive Data Lab

The Interactive Data Lab aims to enhance people’s ability to understand and communicate data through the design of new interactive systems for data visualization and analysis.

Robot Learning lab cover photo of robotic warthog/all terrain vehicle driving in the snow

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 Professor

Associate Professor

Professor


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.

The mission of the UW Center for Research and Education on Accessible Technology and Experiences (CREATE) is to make technology accessible and the world accessible through technology. By bringing together researchers from across the campus, CREATE harnesses the diverse expertise necessary to realize a more just and equitable technological future, one that overcomes existing barriers and ensures new ones do not arise.

Highlights


Allen School News

Professor Magda Balazinska was honored for her influential contributions in data management and data science, while Professor Shwetak Patel was recognized for his groundbreaking work applying computing to health and sustainability.

Forbes

Kim was honored in the health care and sciences category for his work with professor Su-In Lee in the Allen School’s AI for bioMedical Sciences (AIMS) Lab on methods for improving the transparency, safety and explainability of medical AI systems.

Allen School News

In December, Feng was named among the 2026 class of NVIDIA Graduate Fellows in recognition of his work on model collaboration, where “multiple AI models, trained on different data, by different people, and thus possess diverse skills and strengths, collaborate, compose and complement each other.”