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Software & Hardware Systems

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

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Security and Privacy Research Lab

The Security and Privacy Research Lab works on a variety of topics, ranging from studying and addressing security and privacy risks in existing technologies, to anticipating future risks in emerging technologies.

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Sampa

Sampa is an interdisciplinary computer architecture group whose research crosses multiple layers of the system stack, from hardware to programming languages and applications, motivated by new device technologies and applications.


Faculty Members


Centers & Initiatives

The eScience Institute empowers researchers and students in all fields to answer fundamental questions through the use of large, complex, and noisy data. As the hub of data-intensive discovery on campus, we lead a community of innovators in the techniques, technologies, and best practices of data science and the fields that depend on them.

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.