Our mission
The predictions of machine learning (ML) systems often appear fragile, with no hint as to the reasoning behind them—and may be dangerously wrong. This is unacceptable: society must be able to trust and hold to account ML. Our mission is to advance the security and privacy of machine learning. We empower ML developers and engineers to develop and design ML systems that are secure. This often leads us to explore the broader question of what makes a machine learning system trustworthy.
Our team
Our lab is led by Prof. Nicolas Papernot and is located at the University of Toronto and the Vector Institute, both located in downtown Toronto (Canada). Get to know our team by browsing our list of current and past members, and if you are interested in joining please read the following page.
Our work
To learn more about our work, you can find:
- our publications by browsing our papers
- code artifacts released by our lab on our GitHub page
- posts published on our blog
Our sponsors
We would like to acknowledge our sponsors, who support our research with financial and in-kind contributions. Current and past sponsors include Amazon, Apple, Canada Foundation for Innovation, CIFAR, DARPA, DRDC, Ericsson, Intel, Meta, Microsoft, NFRF, NSERC, Ontario, Schmidt Sciences, ServiceNow, Sloan Foundation, University of Toronto, the Vector Institute.