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
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.
RAIVN Lab
The Reasoning, AI, and VisioN (RAIVN) Lab directed by Prof. Ali Farhadi and Prof. Ranjay Krishna focuses at the intersection of computer vision, machine learning, natural language processing and robotics and is targeted towards helping computers…
Allen School Faculty
Professor
Professor
Professor
Professor
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 NSF AI Institute for Agent-based Cyber Threat Intelligence and Operation (ACTION) seeks to change the way mission-critical systems are protected against sophisticated, ever-changing security threats. In cooperation with (and learning from) security operations experts, intelligent agents will use complex knowledge representation, logic reasoning, and learning to identify flaws, detect attacks, perform attribution, and respond to breaches in a timely and scalable fashion.
Highlights
Allen School News
Itani, who works with Allen School professor Shyam Gollakota in the Mobile Intelligence Lab, was recognized for exceptional early-career research advancing AI systems for “superhuman” hearing.
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.