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
Systems Neuroscience & AI Lab (SNAIL)
SNAIL develops computational models and algorithms for understanding how single-trial neural population activity drives our abilities to generate movements, make decisions, and learn from experience.
WEIRD Lab
The Washington Embodied Intelligence and Robotics Development lab is interested in robotics problems, and currently we are thinking deeply about reinforcement learning algorithms to enable real-world robotic manipulation tasks in the home.
Allen School Faculty
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Centers & Initiatives
Globe.AI is a multidisciplinary community of researchers at the University of Washington who aim to create equitable, responsive AI technologies that can adapt to individuals from diverse cultures and communities, including to different norms, languages, behaviors, and communication styles.
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.