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
Information and Communication Technology for Development (ICTD) Lab
The ICTD Lab explores how technology can improve the lives of underserved populations in low-income regions through research spanning HCI, systems, communication and data analytics.
Computer Systems Lab
The Computer Systems Lab works on research covering a number of areas in operating systems, distributed systems, computer architecture and security.
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.
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.
Highlights
GeekWire
After nearly half a century at UW — and at the intersection of Seattle tech, education and civic life — Lazowska is logging off from his official duties. But he’s not completely shutting things down, with plans to stay involved in the community and focus on “the big problems.”
Allen School News
Cardinality estimation helps guide decisions on every aspect of query execution, but current methods often have large errors. To address this, Suciu introduced a more accurate and efficient cardinality estimator, LpBound, which provides a guaranteed upper bound on the query output size.
Allen School News
Balazinska was elected to the WSAS, which provides scientific and technical advice to state policymakers, based on her “contributions in data management for data science, big data systems, cloud computing, and image/video analytics and leadership in data science education.”