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
Robotics and State Estimation Lab
We are interested in the development of computing systems that interact with the physical world in an intelligent way. To investigate such systems, we focus on problems in robotics and activity recognition.
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.
Allen School Faculty
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Associate 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.
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.
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.”