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.
SAMPL
SAMPL is an interdisciplinary machine learning research group exploring problems across the system stack, including deep learning frameworks, specialized hardware for training and inference, new intermediate representations and more.
Faculty Members
Centers & Initiatives
MEM-C is a NSF Materials Research Science and Engineering Center that integrates materials innovations with theory and computation to advance spin-photonic nanostructures and elastic layered quantum materials, aided by an “AI Core” that integrates artificial intelligence-driven materials discovery.
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
WIRED
Professor Shyam Gollakota spoke to WIRED about his work with UW spinout Hearvana leveraging AI to enable people to go beyond noise canceling to customize their soundscape — including selectively amplifying sounds or voices they want to hear while minimizing ones they don’t.
Allen School News
The fellowship will support Zhang’s work in sustainable ubiquitous computing, including the development of recyclable electronics and leveraging artificial intelligence to estimate carbon footprints and provide personalized health insights.
UW News
AI trained on data from the entire internet won’t work equally well for people in different cultures. But when UW researchers fed AI agents data from a kitchen simulation game, they found that the AI absorbed cultural values from observing human behavior — similar to what children do.