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
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.
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…
Faculty Members
Faculty
Faculty
Faculty
Faculty
Centers & Initiatives
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.
TCAT harnesses the power of open-source technology to develop, translate, and deploy accessible technologies, and then sustain them in the hands of communities. Housed by the Paul G. Allen School for Computer Science & Engineering, TCAT centers the experience of people with disabilities as a lens for improving design & engineering, through participatory design practices, tooling and capacity building.
Highlights
Allen School News
Asai (Ph.D., ‘25), research scientist at Ai2 and incoming faculty at Carnegie Mellon University, was recognized for her pioneering research that has helped establish the foundations for retrieval-augmented generation (RAG) and showcase its effectiveness at reducing LLM hallucinations.
Allen School News
Allen School researchers earned multiple awards at the 63rd Annual Meeting of the Association for Computational Linguistics for laying the foundation for how AI systems understand and follow human instructions, exploring how LLMs pull responses from their training data, and more.
UW News
In her new book “Digital Culture Shock: Who Creates Technology and Why This Matters,” Reinecke examines how culture shapes the design and use of technology — and why we should resist a one-size-fits-all approach.