Our researchers are driving innovation across the entire hardware, software and network stack to make computer systems more reliable, efficient and secure.
From internet-scale networks, to next-generation chip designs, to deep learning frameworks and more, we build and refine the devices and applications that individuals, industries and, indeed, entire economies depend upon every day.
Research 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.

Database Group
The Database Group advances both theoretical and systems work in probabilistic databases, stream processing, sensor-based monitoring, databases and the web, XML, image/video data management, data management for machine learning, data mining and more.
Faculty Members
Centers & Initiatives
IFDS organizes its research around four core themes: complexity, robustness, closed-loop data science, and ethics and algorithms. By making concerted progress on these fundamental fronts, IFDS aims to lower several of the barriers to better understanding of data science methodology and to its improved effectiveness and wider relevance to application areas.
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.
Highlights
Allen School News
Allen School News
Allen School News