Nicolas Papernot

Nicolas Papernot

I am an Assistant Professor at the University of Toronto, in the Departments of Electrical and Computer Engineering and of Computer Science. I am also a faculty member at the Vector Institute where I hold a Canada CIFAR AI Chair, and a faculty affiliate at the Schwartz Reisman Institute.

My research interests are at the intersection of security, privacy, and machine learning. If you would like to learn more about my research, I recommend reading the blog posts I co-authored on cleverhans.io, for example about proof-of-learning, collaborative learning beyond federation, dataset inference, machine unlearning, differentially private ML, or adversarial examples.

My research has been cited in the press, including the New York Times, Popular Science, and Wired. I currently serve as an Associate Chair of the IEEE Symposium on Security and Privacy. I earned my Ph.D. in Computer Science and Engineering at the Pennsylvania State University, working with Prof. Patrick McDaniel and supported by a Google PhD Fellowship. Upon graduating, I spent a year at Google Brain where I still spend some of my time.

Email: [email protected]

Office: Pratt 484E and MaRS Suite 710

Mail/Packages: 10 King's College Road, Room SFB540, Toronto, ON M5S 3G4, Canada

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Selected publications

A complete list of publications is available in my CV.

Research group

Current students and postdocs
Past students and postdocs
Information for prospective graduate students and postdocs

Research Talks

Upcoming

Here is a list of talks I will be giving. Feel free to reach out if you will be attending one of these events and would like to meet.

Past Recorded Talks

These video resources are a good overview of my research interests.

Tempered Sigmoids for DP-SGD
Trustworthy ML
Deepfakes
Lecture on ML security and privacy
Privacy-preserving ML
Adversarial examples

Blog Posts

Here is a list of blog posts discussing some of the research questions I'm interested in:

Teaching