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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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Interactive Data Lab

The Interactive Data Lab aims to enhance people’s ability to understand and communicate data through the design of new interactive systems for data visualization and analysis.

Closeup of silicon chip technology

Bespoke Silicon Group

The Bespoke Silicon Group aims to bring hardware design to its highest art and rapidly conceive of, design and implement entirely new kinds of hardware faster than has ever been done before.


Allen School Faculty

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Centers & Initiatives

MEM-C is a NSF Materials Research Science and Engineering Center that integrates materials innovations with theory and computation to advance spin-photonic nanostructures and elastic layered quantum materials, aided by an “AI Core” that integrates artificial intelligence-driven materials discovery.

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.

Highlights


KUOW Soundside

Researcher Chris Takahashi describes how the Molecular Information Systems Lab encoded historical documents from the Library of Congress in synthetic DNA for a time capsule marking America’s 250th anniversary.

UW News

Professors David Kohlbrenner and Franziska Roesner (Ph.D., ‘14) of the Allen School’s Privacy & Security Research Lab found that browser agents are susceptible to cyberattacks by violating the same-origin policy, a cornerstone of modern web security that has safeguarded users for 30 years.

UW News

A team led by Allen School professor Vikram Iyer and Ph.D. student Zhihan Zhang published a paper in Nature Electronics describing a system that can assemble life cycle assessments, or LCAs, for electronic devices in about a minute with the help of AI agents.