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
Makeability Lab
The Makeability Lab specializes in Human-Computer Interaction and applied machine learning for high-impact problems in accessibility, computational urban science, and augmented reality.
UbiComp Lab
The Ubiquitous Computing (UbiComp) Lab develops innovative systems for health sensing, low-power sensing, energy sensing, activity recognition and novel user interface technology for real-world applications.
Allen School Faculty
Associate Professor
Associate Professor
Associate Professor
Associate Professor
Centers & Initiatives
Society + Technology is a cross-campus, cross-disciplinary initiative and community at the University of Washington that is dedicated to research, teaching and learning focused on the social, societal and justice dimensions of technology.
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.
Highlights
Allen School News
Professor Magda Balazinska was honored for her influential contributions in data management and data science, while Professor Shwetak Patel was recognized for his groundbreaking work applying computing to health and sustainability.
Forbes
Kim was honored in the health care and sciences category for his work with professor Su-In Lee in the Allen School’s AI for bioMedical Sciences (AIMS) Lab on methods for improving the transparency, safety and explainability of medical AI systems.
Allen School News
In December, Feng was named among the 2026 class of NVIDIA Graduate Fellows in recognition of his work on model collaboration, where “multiple AI models, trained on different data, by different people, and thus possess diverse skills and strengths, collaborate, compose and complement each other.”