Current students

Extremophiles are species that are adapted to live at the edges of biological tolerance, in a range of environments that seem inhospitable to life by human standards. These extremely hardy organisms are found in all three domains and all six kingdoms of life, the highest and second highest levels of classification biologists use to categorize living things based on common ancestry.

Please note: This master’s thesis presentation will take place in DC 2310.

Prabhjot Singh, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Diogo Barradas

Although encrypted channels, like those provided by anonymity networks such as Tor, have been put into effect, network adversaries have proven their capability to undermine users’ browsing privacy through website fingerprinting attacks.

Please note: This master’s thesis presentation will take place online.

Fadhil Abubaker, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Khuzaima Daudjee

Please note: This master’s thesis presentation will take place online.

Seba Khaleel, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Samer Al-Kiswany

Please note: This master’s thesis presentation will take place in DC 3317.

Adrian Cruzat La Rosa, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Diogo Barradas

Friday, January 12, 2024 12:00 pm - 1:00 pm EST (GMT -05:00)

PhD Seminar • Artificial Intelligence • Learning Voting Rules Using Neural Networks

Please note: This PhD seminar will take place online.

Ben Armstrong, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Kate Larson

We present our work using machine learning models to approximate social choice functions, a.k.a. methods of voting. Voting rules are functions that are given voter preferences and produce a winning candidate.

Please note: This master’s thesis presentation will take place in DC 2310 and online.

Sonja Linghui Shan, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jeffrey Shallit

Please note: This master’s thesis presentation will take place in DC 2314, not DC 3317. 

Lucas Fenaux, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Florian Kerschbaum

New research into large language models shows that they repeat conspiracy theories, harmful stereotypes, and other forms of misinformation.

In a recent study, researchers at the Cheriton School of Computer Science systematically tested an early version of ChatGPT’s understanding of statements in six categories: facts, conspiracies, controversies, misconceptions, stereotypes, and fiction. This was part of the researchers’ efforts to investigate human-technology interactions and explore how to mitigate risks.