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
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.
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.
Allen School Faculty
Assistant Professor
Professor
Professor
Professor
Centers & Initiatives
IFDS organizes its research around four core themes: complexity, robustness, closed-loop data science, and ethics and algorithms. By making concerted progress on these fundamental fronts, IFDS aims to lower several of the barriers to better understanding of data science methodology and to its improved effectiveness and wider relevance to application areas.
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.
Highlights
Allen School News
Researchers in the Programming Languages & Software Engineering (PLSE) group introduced egg, an open-source library that uses e-graphs along with equality saturation to optimize term representations. Their paper was recently featured as a Communications of the ACM Research Highlight.
Allen School News
Grossman, who has served as vice director of the school for the past nine years and is a recognized leader in programming languages education and research, will succeed Magdalena Balazinska at the conclusion of her term on August 17.
Allen School News
In the award-winning paper, Nirkhe and his collaborators resolved a longstanding problem in quantum complexity theory by proving that quantum proofs are computationally more powerful than classical proofs.