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
Human-Centered Robotics Lab
In the Human-Centered Robotics lab we aim to develop robotics that are useful and usable for future users of task-oriented robots.
Make4all Group
Make4all Group creates solutions that empower people with disabilities to accomplish their goals, applying technologies such as 3D printing, knitting and other fabrication technologies to improve inclusion in and accessibility of our digital future.
Faculty Members
Centers & Initiatives
The Tech Policy Lab is a unique, interdisciplinary collaboration at the University of Washington that aims to enhance technology policy through research, education, and thought leadership. Founded in 2013 by faculty from the Paul G. Allen School of Computer Science & Engineering, Information School, and School of Law, the Lab aims to bridge the gap between technologists and policymakers and to help generate wiser, more inclusive tech policy.
The mission of the UW Center for Research and Education on Accessible Technology and Experiences (CREATE) is to make technology accessible and the world accessible through technology. By bringing together researchers from across the campus, CREATE harnesses the diverse expertise necessary to realize a more just and equitable technological future, one that overcomes existing barriers and ensures new ones do not arise.
Highlights
Allen School News
A team of Allen School and Ai2 researchers were recognized for developing an efficient, scalable system for indexing petabyte-level text corpora with minimal storage overhead to better understand the data on which large language models are trained.
Allen School News
Allen School researchers led the development of a benchmark dataset of 26,000 real-world, open-ended queries to evaluate the creative generation of large language models. They discovered major LLMs all generate similar outputs as if they’re part of an Artificial Hivemind.
Business Insider
Farhadi, who co-leads the Allen School’s Reasoning, AI, and VisioN (RAIVN) Lab and is also CEO of the Allen Institute for Artificial Intelligence (Ai2), was recognized for his leadership in open AI research and his influence on how institutions scale AI for the benefit of humanity.