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.
News
- Jan. 18, 2021Is WiFi too polite?
The following is an article by Dr. Ali Abedi, a lecturer at the Cheriton School of Computer Science. Dr. Abedi’s article appeared originally on APNIC Blog.
- Jan. 12, 2021Cheriton School of Computer Science Professor Ihab Ilyas named ACM Fellow
Professor Ihab Ilyas has been named a 2020 ACM Fellow for his contributions to data cleaning and data integration.
- Jan. 5, 2021Cheriton School of Computer Science researchers named Vector Institute Faculty Affiliates
Cheriton School of Computer Science Professors Ihab Ilyas and Gautam Kamath are among the 72 faculty members appointed as 2020 Faculty Affiliates at the Vector Institute. The 2020 cohort includes both new faculty affiliates as well as those returning for a second term.
The Vector Institute’s Faculty Affiliates program brings together professors who conduct research in deep learning, machine learning and artificial intelligence across universities in Ontario.
Events
- Jan. 22, 2021Master’s Thesis Presentation • Formal Methods — Linking Alloy with SMT-based Finite Model Finding
Plese note: This master’s thesis presentation will be given online.
Khadija Tariq, Master’s candidate
David R. Cheriton School of Computer ScienceSupervisor: Professor Nancy Day
- Jan. 25, 2021Master’s Thesis Presentation • Algorithms and Complexity — Counting Flimsy Numbers via Formal Language Theory
Please note: This master’s thesis presentation will be given online.
Trevor Clokie, Master’s candidate
David R. Cheriton School of Computer ScienceSupervisor: Professor Jeffrey Shallit
- Jan. 26, 2021Seminar • Algorithms and Complexity — Diversity and Fairness in Data Summarization Algorithms
Please note: This seminar will be given online.
Sepideh Mahabadi
Toyota Technological Institute at ChicagoSearching and summarization are two of the most fundamental tasks in massive data analysis. In this talk, I will focus on these two tasks from the perspective of diversity and fairness.