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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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Behavioral Data Science Group

The Behavioral Data Science Group leverages large-scale behavioral data to extract actionable insights about our lives, health and happiness by combining techniques from data science, social network analysis, and natural language processing.

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Mobile Intelligence Lab

The interdisciplinary Mobile Intelligence Lab builds intelligent systems and tools for tackling hard technical and societal problems, including battery-free computing, medical diagnostics, augmented human perception and more.


Faculty Members

Faculty


Centers & Initiatives

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Institute for Medical Data Science (IMDS)

The Institute forMedical Data Science (IMDS) is a joint effort among the Schools of Medicine and Public Health and the College of Engineering, including the Allen School to lead the development and implementation of cutting-edge AI and data science methods in medical data science. By harnessing the power of AI across diverse health determinants, IMDS aims to improve patient health, provider satisfaction, and healthcare operations, particularly in the Pacific Northwest region.

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Computing for the Environment (CS4Env)

Computing for the Environment (CS4Env) at the University of Washington supports novel collaborations across the broad fields of environmental sciences and computer science & engineering. The initiative engages environmental scientists and engineers, computer scientists and engineers, and data scientists in using advanced technologies, methodologies and computing resources to accelerate research that addresses pressing societal challenges related to climate change, pollution, biodiversity and more.

Highlights