Our study of the theoretical foundations of computing spans algorithm design and analysis, complexity, optimization, cryptography, quantum and more.
We seek to answer fundamental and long-standing questions about the capabilities and limitations of our field, which has practical implications in economics, logistics, social welfare, transportation and many other real-world domains.
Research Groups & Labs
![group-lab-cryptography-padlocks Three padlocks of different sizes linked by a chain](https://www.cs.washington.edu/wp-content/uploads/2024/06/group-lab-cryptography-padlocks.jpg)
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.
![group-lab_database-group Database Group cover image of a mountain](https://www.cs.washington.edu/wp-content/uploads/2024/05/group-lab_database-group.jpg)
Database Group
The Database Group advances both theoretical and systems work in probabilistic databases, stream processing, sensor-based monitoring, databases and the web, XML, image/video data management, data management for machine learning, data mining and more.
Faculty Members
Centers & Initiatives
![center-uw-memc-logo UW MEM-C logo](https://www.cs.washington.edu/wp-content/uploads/2024/12/center-uw-memc-logo.jpg)
Molecular Engineering Materials Center (UW-MEMC)
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.
![centers-escience-institute eScience Institute logo](https://www.cs.washington.edu/wp-content/uploads/2024/10/centers-escience-institute.jpg)
eScience Institute
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
![news-massively-parallel-communication Black and white parallel lines created by window blinds and shadow](https://www.cs.washington.edu/wp-content/uploads/elementor/thumbs/news-massively-parallel-communication-qyof24xke93twngw7w72a96s5o68ycv0usi5sb25i8.jpg)
A chance encounter helped Paul Beame, Paris Koutris (Ph.D., ‘15) and Dan Suciu create the award-winning MPC model that aids scientists in understanding some of the deeper nuances surrounding big data management.
Allen School News
![news-oveis-gharan-smale-prize-profile Shayan Oveis Gharan](https://www.cs.washington.edu/wp-content/uploads/elementor/thumbs/news-oveis-gharan-smale-prize-profile-qyode8nswb4236gzz04wedbdfre8gp2rybyavjva00.jpg)
Shayan Oveis Gharan has all the ingredients of a trailblazing researcher who also happens to be a genuinely nice guy. The combination has proved to be a genuine recipe for success, as he has racked up a series of results — and accolades — in theoretical computer science.
Allen School News
![news-theory-focs-rothvoss A tractor in a sunlit field](https://www.cs.washington.edu/wp-content/uploads/elementor/thumbs/news-theory-focs-rothvoss-qyo7rys46s7po2ac42i4bwvffqdp1j27t5zq0xs6zk.jpg)
After more than 30 years of stalled progress in the field, Victor Reis and Thomas Rothvoss of the Allen School’s Theory of Computation group earned a FOCS Best Paper award for nearly resolving the Subspace Flatness Conjecture for fast integer programming.