Nicolas Papernot

@nicolaspapernot.bsky.social

Security and Privacy of Machine Learning at UofT, Vector Institute, and Google 🇨🇦🇫🇷🇪🇺 Co-Director of Canadian AI Safety Institute (CAISI) Research Program at CIFAR. Opinions mine

📄 Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings (✨ oral paper ✨) Paper ➡️ arxiv.org/abs/2505.22356 Poster ➡️ E-504 on Thu 17 Jul 4:30 p.m. — 7 p.m. Oral Presentation ➡️ West Ballroom C on Thu 17 Jul 4:15 p.m. — 4:30 p.m.

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📢 New ICML 2025 paper! Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention 🤔 Think model uncertainty can be trusted? We show that it can be misused—and how to stop it! Meet Mirage (our attack💥) & Confidential Guardian (our defense🛡️). 🧵1/10

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As part of the theme Societal Aspects of Securing the Digital Society, I will be hiring PhD students and postdocs at #MPI-SP, focusing in particular on the computational and sociotechnical aspects of technology regulations and the governance of emerging tech. Get in touch if interested.

Congratulations again, Stephan, on this brilliant next step! Looking forward to what you will accomplish with @randomwalker.bsky.social & @msalganik.bsky.social!

Stephan Rabanser@stvrb.bsky.social · 2y ago

Starting off this account with a banger: In September 2025, I will be joining @princetoncitp.bsky.social at Princeton University as a Postdoc working with @randomwalker.bsky.social & @msalganik.bsky.social! I am very excited about this opportunity to continue my work on trustworthy/reliable ML! 🥳

One of the first components of the CAISI (Canadian AI Safety Institute) research program has just launched: a call for Catalyst Grant Projects on AI Safety. Funding: up to 100K for one year Deadline to apply: February 27, 2025 (11:59, AoE) More details: cifar.ca/ai/cifar-ai-...

CIFAR AI Catalyst Grants - CIFAR

Encouraging new collaborations and original research projects in the field of machine learning, as well as its application to different sectors of science and society.

cifar.ca

If you work at the intersection of security, privacy, and machine learning, or more broadly how to trust ML, SaTML is a small-scale conference with highly-relevant work where you'll be able to have high-quality conversations with colleagues working in your area.

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