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photo of Professor Pengyu Nie
Monday, March 11, 2024

Meet Pengyu Nie, a professor who uses machine learning and natural language processing to improve software engineering

Pengyu Nie obtained his PhD in 2023 and MSc in 2020 from The University of Texas at Austin, where he was advised by Milos Gligoric. He has a BSc from University of Science and Technology of China, which he received in 2017.

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Friday, March 8, 2024

International Women’s Day: Celebrating five Cheriton School of Computer Science researchers

Friday, March 8, 2024 marks International Women’s Day, a global holiday recognizing gender-related issues and honouring female achievements. To celebrate, the Cheriton School of Computer Science is highlighting five female students and faculty who paved significant research breakthroughs this past year.  

Friday, March 15, 2024 2:00 pm - 3:00 pm EDT (GMT -04:00)

CrySP Speaker Series on Privacy • Zero-Knowledge Proofs Beyond Circuits and Constraints — How to Efficiently Build a “ZK CPU”

Please note: This CrySP Speaker Series on Privacy talk will take place in DC 1302 and online.

Yibin Yang, PhD candidate
School of Computer Science, Georgia Institute of Technology

Friday, March 22, 2024 1:30 pm - 2:30 pm EDT (GMT -04:00)

Master’s Thesis Presentation • Software Engineering • Mitigating the Uncertainty and Imprecision of Log-Based Code Coverage Without Requiring Additional Logging Statements

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

Xiaoyan Xu, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Shane McIntosh

Monday, April 8, 2024 11:00 am - 12:00 pm EDT (GMT -04:00)

Master’s Thesis Presentation • Data Systems • Explaining Expert Search and Team Formation Systems with ExES

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

Kiarash Golzadeh, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Lukasz Golab

photo of Lesley Istead, Andreea Pocol, Sabrina Mokhtari
Thursday, March 7, 2024

Cheriton researchers find that survey participants duped by AI-generated images nearly 40 per cent of the time

If you have trouble figuring out if an image of a person is real or if it’s been generated using artificial intelligence, you’re not alone.

A new study conducted by Cheriton School of Computer Science researchers found that people had more difficulty than expected distinguishing who is a real person and who is artificially generated.

The study saw 260 participants provided with 20 unlabeled pictures: 10 of which were of real people obtained from Google searches, and the other 10 generated by Stable Diffusion or DALL-E, two commonly used AI programs that generate images.