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
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.
SAMPL
SAMPL is an interdisciplinary machine learning research group exploring problems across the system stack, including deep learning frameworks, specialized hardware for training and inference, new intermediate representations and more.
Faculty Members
Centers & Initiatives
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.
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.
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.