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
Programming Languages & Software Engineering Group (PLSE)
The Programming Languages and Software Engineering Group advances fundamental research and practical applications in programming environments, program analysis, language design, synthesis, compilers, testing, verification and security.
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.
Allen School Faculty
Assistant Professor
Professor
Professor & Vice Director
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.
The NSF AI Institute for Agent-based Cyber Threat Intelligence and Operation (ACTION) seeks to change the way mission-critical systems are protected against sophisticated, ever-changing security threats. In cooperation with (and learning from) security operations experts, intelligent agents will use complex knowledge representation, logic reasoning, and learning to identify flaws, detect attacks, perform attribution, and respond to breaches in a timely and scalable fashion.
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.