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
Computer Systems Lab
The Computer Systems Lab works on research covering a number of areas in operating systems, distributed systems, computer architecture and security.
Cryptography Research Group
The Cryptography Group advances the foundations and applications of cryptography, including public-key and symmetric cryptography, obfuscation, attribute-based and functional encryption, secure multi-party computation, quantum cryptography and more.
Allen School Faculty
Professor
Associate Professor
Assistant Professor
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Centers & Initiatives
AI@UW aims to push the boundaries of AI technology in service to the public good by advancing ethical, interdisciplinary AI research while fostering practical innovation to benefit society at large.
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
Researchers in the Programming Languages & Software Engineering (PLSE) group introduced egg, an open-source library that uses e-graphs along with equality saturation to optimize term representations. Their paper was recently featured as a Communications of the ACM Research Highlight.
Allen School News
Grossman, who has served as vice director of the school for the past nine years and is a recognized leader in programming languages education and research, will succeed Magdalena Balazinska at the conclusion of her term on August 17.
Allen School News
In the award-winning paper, Nirkhe and his collaborators resolved a longstanding problem in quantum complexity theory by proving that quantum proofs are computationally more powerful than classical proofs.