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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

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UbiComp Lab

The Ubiquitous Computing (UbiComp) Lab develops innovative systems for health sensing, low-power sensing, energy sensing, activity recognition and novel user interface technology for real-world applications.

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

Professor

Assistant Professor


Centers & Initiatives

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.

The AI Institute for Societal Decision Making (AI-SDM) brings together AI and social sciences researchers to develop human-centric AI for societal good that harnesses the power of data and improved understanding of human decisions to create better and more trusted choices.

Highlights


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.”

Institute for Foundations of Data Science

The International Conference on Artificial Intelligence and Statistics (AISTATS) recognized Jamieson for his 2016 paper underpinning an approach to hyperparameter optimization that has been widely adopted within the machine learning community.

Allen School News

Multiple Allen School authors received Best Paper Awards or honorable mentions for their work on interactive systems that enable more flexible human-AI agent collaboration, an AI-based tool that helps screen-reader users make sense of geovisualizations, and more.