David R. Cheriton School of Computer Science

The Cheriton School of Computer Science is named for David R. Cheriton, who earned his PhD in Computer Science at the University of Waterloo in 1978. In 2005, Professor Cheriton made a transformational gift to the school that supports named chairs, faculty fellowships, and graduate scholarships.

Discover our latest achievements by following our news. Upcoming talks on a range of computer science topics are found under events.
 
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News

Professor Freda Shi was featured in Toyota Technological Institute at Chicago's (TTIC), alumni highlight series.

Freda Shi, Ph.D. graduate from TTIC’s class of 2024 (advised by Professors Karen Livescu and Kevin Gimpel), joined the Cheriton School of Computer Science at the University of Waterloo as a tenure-track Assistant Professor in July 2024. In September 2024 she was named a CIFAR AI Chair and a faculty member at the Vector Institute.

Freda’s research focuses on computational linguistics and natural language processing, aiming to deepen the understanding of both natural language and human language processing. She explores how these insights can enhance the design of more efficient, effective, safe, and trustworthy NLP systems. She is particularly interested in learning language through grounding, computational multilingualism, and related machine learning aspects.

Seventeen students from the University of Waterloo and Wilfred Laurier University dominated ETHDenver, held from February 23 to March 2, 2025.

ETHDenver is the world’s largest and longest-running Ethereum event. Since 2018, it has hosted blockchain-focused events, including panel discussions, workshops, networking sessions, and boot camps. Their main event is #BUIDLathon, a hackathon where attendees can team up to develop their own blockchain projects.

Professor Xiao Hu has received a Best Paper Award at the 2025 ACM SIGMOD/PODS International Conference on Management of Data for her research on optimizing join-aggregate queries.

Her paper, Output-Optimal Algorithms for Join-Aggregate Queries, addresses a long-standing open problem in database theory, establishing output-optimal bounds on the efficiency with which such queries can be processed.

Events