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Monday, April 8, 2024 9:00 am - 10:00 am EDT (GMT -04:00)

PhD Seminar • Computational Neuroscience | Artificial Intelligence | Machine Learning • How Predictive Coding Rescues Traditional Neural Networks on Adversarial Examples

Please note: This PhD seminar will take place in DC 2310 and online.

Ehsan Ganjidoost, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jeff Orchard

photo of Professor Yaoliang Yu in Davis Centre
Thursday, March 21, 2024

Yaoliang Yu receives Ontario Early Researcher Award to develop pushing-forward deep generative models

Professor Yaoliang Yu has been awarded $100,000 by the Ministry of Colleges and Universities Early Researcher Awards program to develop deep generative machine learning models. The Ministry’s amount is matched by an additional $50,000 from the University of Waterloo, bringing the total funding to $150,000 to support one PhD, two master’s, and a number of undergraduate students over five years.

composite image of CS student Jessica Bohm in front of CERN’s Large Hadron Collider
Wednesday, March 20, 2024

Computer Science student Jessica Bohm receives Co-op Student of the Year award

Jessica Bohm, a fourth-year Computer Science student, is one of six Waterloo students to receive a 2023 Co-op Student of the Year award.

Wednesday, March 27, 2024 12:30 pm - 1:30 pm EDT (GMT -04:00)

PhD Seminar • Differential Privacy | Data Cleaning • Differentially Private Data Generation with Missing Data

Please note: This PhD seminar will take place in DC 1304 and online.

Shubhankar Mohapatra, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Xi He

Despite several works that succeed in generating synthetic data with differential privacy (DP) guarantees, they are inadequate for generating high-quality synthetic data when the input data has missing values.

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

Master’s Thesis Presentation • Cryptography, Security, and Privacy (CrySP) • ProofFrog: A Tool For Verifying Game-Hopping Proofs

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

Ross Evans, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Douglas Stebila

Wednesday, March 27, 2024 10:30 am - 11:30 am EDT (GMT -04:00)

Seminar • Artificial Intelligence • Mathematical Foundations for Trustworthy Machine Learning

Please note: This seminar will take place in DC 1304.

Lunjia Hu, PhD candidate
Computer Science Department, Stanford University

Machine learning holds significant potential for positive societal impact. However, in critical applications involving people such as healthcare, employment, and lending, machine learning raises serious concerns of fairness, robustness, and interpretability. Addressing these concerns is crucial for making machine learning more trustworthy.