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
Sensor Systems Laboratory
The Sensor Systems Laboratory invents new sensor systems, devises new ways to power and communicate with them, and develops algorithms for using them, with applications in the domains of bioelectronics, robotics, and ubiquitous computing.
Systems Neuroscience & AI Lab (SNAIL)
SNAIL develops computational models and algorithms for understanding how single-trial neural population activity drives our abilities to generate movements, make decisions, and learn from experience.
Faculty Members
Centers & Initiatives
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.
Computing for the Environment (CS4Env) at the University of Washington supports novel collaborations across the broad fields of environmental sciences and computer science & engineering. The initiative engages environmental scientists and engineers, computer scientists and engineers, and data scientists in using advanced technologies, methodologies and computing resources to accelerate research that addresses pressing societal challenges related to climate change, pollution, biodiversity and more.
Highlights
Allen School News
Professors Simon Shaolei Du and Ranjay Krishna, and Sewon Min (Ph.D., ‘24), now faculty at University of California, Berkeley and a research scientist at Ai2, were honored by MIT Technology Review for their work in AI, large language models, computer vision and more.
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.