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.
News
Scoring high with AI
Two Cheriton alumni, David Radke and Kyle Tilbury, are using AI to make it easier for researchers to unlock sports insights— which were previously reserved for pro-teams.
By leveraging the Google Research Football’s reinforcement learning environment, the duo created a system that can simulate and record unlimited soccer matches. They generated and saved data from 3,000 simulated soccer games, resulting in a rich and complex dataset of passes, goals, and player movements for researchers to study.
Gamifying AI
Around 30% of Canadians rely on AI for personal and work use, from proofreading work emails to planning trips— but do we truly understand how AI works?
In today’s world, AI may dictate our everyday outcomes and choices more often than man-made decisions. Even the most essential sectors are adopting AI. Self-driving cars, a game-changer in transportation, use AI to sense its surroundings and control its movements. Some clinics are employing object detection and recognition models, a form of AI, to detect cancerous tumours from X-ray scans— and do it at a much faster and more accurate rate than human doctors.
You’re better at spotting malware than you think
When it comes to cybersecurity, humans are often seen as the weakest link, but new research suggests that with a little help, people can do a surprisingly effective job at identifying malware.
In a first-of-its-kind study, researchers from the Cheriton School of Computer Science teamed up with University of Guelph cybersecurity experts to test how users, ranging from tech novices to experts, can respond to real-time legitimate and malicious software download requests in a simulated office setting.
Events
Master’s Thesis Presentation • Systems and Networking • Combining High-Level-Synthesis and Register-Transfer Level Design for Programmable Hardware
Please note: This master’s thesis presentation will take place in DC 2314.
Kimiya Mohammadtaheri, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Mina Tahmasbi Arashloo
Master’s Thesis Presentation • Artificial Intelligence • Demystifying Foreground-Background Memorization in Diffusion Models
Please note: This master’s thesis presentation will take place in DC 2310.
Jimmy Di, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Gautam Kamath
PhD Seminar • Machine Learning • Universal Physics-Informed Neural Networks and their Applications
Please note: This PhD seminar will take place in DC 2314.
Lena Podina, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Ali Ghodsi and Mohammad Kohandel