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.
Quantum Group
The Quantum Group does research on a variety of topics in quantum information and computation (primarily on the theory side), including quantum complexity theory, error-correction, cryptography, algorithms, and learning.
Faculty Members
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 UW Center for the Future of Cloud Infrastructure (FOCI) aims to foster a tight partnership between practitioners and researchers in both industry and academia to define the next generation of cloud infrastructure to achieve new levels of security, reliability, performance along with cost-efficiency and environmental sustainability.
Highlights
Allen School News
Armon Dadgar (B.S., ‘11) co-founded the high-flying cloud company HashiCorp inspired by an undergraduate research project. Now he and partner Joshua Kalla hope to sow the seeds of the next HashiCorp with a new professorship and support for a new generation of innovators and entrepreneurs.
Allen School News
Deeds introduced partition constraints, a new approach for making conjunctive query executions more efficient. He presented the research at the 28th International Conference on Database Theory (ICDT), earning both the Best Student Paper and Best Paper Awards.
Allen School News
A team of Allen School researchers introduced computational illusion knitting — a design framework that helps automate the process, making illusion knitting more accessible and allowing for more complex and multi-view patterns like hidden Mona Lisas that were previously believed to be impossible.