Welcome to the 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 in 1978, and made a transformational gift to the school in 2005. It has become the largest academic concentration of Computer Science researchers in Canada.  

Discover our latest achievements by following our news and events.
Please go to contact, open positions or visit if you have a question about school programs or services, would like to know more about faculty positions available or plan to visit our school.
  1. Feb. 18, 2020Beyond Tradition – A documentary about Waterloo and its early days in computer science research and application
    Screen grab of Wes Graham, Waterloo's father of computing

    Distinguished Professor Emeritus Ken McLaughlin has spent his career uncovering and shaping the stories of our local communities into urban portraits that breathe with the life of great biographies. 

  2. Feb. 17, 2020AI should not leave structured data behind

    The following is an article written by Professor Ihab Ilyas, a faculty member of the Cheriton School of Computer Science’s Data Systems Group and the Thomson Reuters Research Chair in Data

  3. Jan. 31, 2020Jason Hu and Ondrej Lhoták receive a Distinguished Paper Award at POPL 2020

    Recent MMath graduate Jason Hu and Cheriton School of Computer Science Professor Ondřej Lhoták have received a Distinguished Paper Award at POPL 2020, the 47thACM SIGPLAN Symposium on Principles of Programming Languages.

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  1. Feb. 26, 2020PhD Seminar • Data Systems — Dynamic Early Exiting for Accelerating BERT Inference

    Ji Xin, PhD candidate
    David R. Cheriton School of Computer Science

  2. Feb. 26, 2020Seminar • Computer Algebra — An Efficient Sum of Squares Certificate for 4-ary 4-ic

    Dmitrii Pasechnik, Department of Computer Science
    University of Oxford

  3. Feb. 26, 2020Seminar • Waterloo AI Institute — Noise Flow: Noise with Conditional Normalizing Flows

    Marcus Brubaker
    Department of Electrical Engineering and Computer Science, York University
    Research Director, Borealis AI

    Modelling and synthesizing image noise is an important aspect in many computer vision applications. The long-standing additive white Gaussian and heteroscedastic (signal-dependent) noise models widely used in the literature provide only a coarse approximation of real sensor noise.

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