WebNotice

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

Sarah Cen, PhD candidate
Electrical Engineering and Computer Science Department, MIT

We have begun grappling with difficult questions related to the rise of AI, including: What rights do individuals have in the age of AI? When should we regulate AI and when should we abstain? What degree of transparency is needed to monitor AI systems? These questions are all concerned with AI accountability: determining who owes responsibility and to whom in the age of AI.

Please note: This CrySP Speaker Series on Privacy talk will take place in MC 5501 and online.

Kathrin Hövelmanns, Tenured Assistant Professor
Applied and Provable Security group, TU Eindhoven

Please note: This seminar will take place online.

Philip A. Bernstein
Distinguished Scientist, Microsoft Research
Affiliate Professor, University of Washington

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

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

Joseph Musleh, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Éric Schost

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.

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

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

Murray Dunne, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Sebastian Fischmeister

Please note: This PhD seminar will take place online.

Miti Mazmudar, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Ian Goldberg

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.