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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

Dexterous robotic hand reaching to lift rectangular brick

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.

Professor Dieter Fox and a student demonstrate a remote operated robotic arm attempting to pick up a block

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.


Allen School Faculty

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Centers & Initiatives

The Institute for Medical 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.

The Science Hub supports a broad set of programs — including fellowships for doctoral students, collaboration among researchers and support for collaborative research events — designed to accelerate artificial intelligence (AI), robotics and engineering in the Seattle area.

Highlights


HearingTracker

A technology known as semantic hearing developed in Allen School professor Shyam Gollakota’s lab could let users create acoustic bubbles, isolate chosen voices, and control individual sounds in their environment.

MIT Technology Review Korea

Allen School professor Su-In Lee discusses the role of artificial intelligence in science and medicine and explains why the process the model follows to arrive at an answer is as important as the answer itself.

Fast Company

Allen School professor Jon Froehlich talks about how Project Sidewalk empowers communities by crowdsourcing data on pedestrian infrastructure, from curb ramps to broken pavement, to improve accessibility.