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
UW NLP Group
The University of Washington Natural Language Processing Group comprises diverse researchers across campus collaborating in the study of all aspects of NLP from computational, engineering, linguistic, social, statistical, and other perspectives.
Neural Systems Lab
The Neural Systems Lab at the UW focuses on understanding the brain using computational models and simulations, and applying this knowledge to the task of developing human-like artificial intelligence (AI) and brain-computer interfaces (BCIs).
Faculty Members
Centers & Initiatives
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.
The interdisciplinary DUB group at the University of Washington advances research, collaboration and teaching related to the interaction between design, people, and technology.
Highlights
Allen School News
Allen School Ph.D. student Cheng-Yu Hsieh is interested in tackling one of the biggest challenges in today’s large-scale machine learning environment — how to make AI development more accessible. His research focuses on making both data and model scaling more efficient and affordable.
Allen School News
A team of University of Washington and NVIDIA researchers developed FlashInfer, a versatile inference kernel library that can help make large language models faster and more adaptable, and received a Best Paper Award at MLSys 2025 for their work.
Allen School News
Sharma (Ph.D., ‘24) won the 2024 award from the Association for Computing Machinery for leveraging AI to make high-quality mental health support more accessible, and Min (Ph.D., ‘24) received an honorable mention for developing a new class of efficient and flexible language models.