Professor Melanie A. Woodin
President, University of Toronto

invites you to join the Schwartz Reisman Institute for Technology and Society for a timely conversation on how artificial intelligence is reshaping cybersecurity and what it means for our increasingly connected world. 

Featuring Dr. Nicolas Papernot, Associate Professor of Electrical and Computer Engineering and an expert in AI security, alongside other leading voices in the field, this discussion will explore opportunities and risks emerging from rapid advances in artificial intelligence. Professor Papernot and his team recently discovered a new class of cyberthreat that can be built with open-weight AI models, giving hackers more power and reach at far less cost.

Drawing on University of Toronto research, speakers will examine what new AI capabilities such as Papernot’s recent discovery mean for critical digital infrastructure, the economy, and national security, and how independent research, stronger safeguards, and cross-sector collaboration can help Canada prepare for the risks ahead.

Moderated by: Alexandra Posadzki 
Financial and cybercrime reporter, The Globe and Mail

Register to watch the event live. If you're unable to attend, a recording will be sent to all registrants.

About the Speaker 

Nicolas Papernot is an Associate Professor of Electrical and Computer Engineering at the University of Toronto and a Faculty Member at the Vector Institute where he holds a Canada CIFAR AI Chair. His research interests are broadly at the intersection of computer security, privacy, and machine learning.

Professor Papernot earned his PhD degree in Computer Science and Engineering from the Pennsylvania State University supported by a Google PhD Fellow in Security and Privacy. His PhD research focused on characterizing the attack surface of machine learning systems and inventing defense mechanisms to improve their security and privacy. Prior to joining the University of Toronto, Nicolas spent a year as a research scientist at Google Brain.

His work has been applied in industry and academia to evaluate and improve the robustness of machine learning models, to input perturbations known as adversarial examples, as well as to deploy machine learning with privacy guarantees for training data at industry scale. He was invited to write technical articles for the CACM and IEEE Security and Privacy Magazine. Nicolas is a program committee member of ACM CCS, IEEE S&P, and USENIX Security. He also reviews for ICML, ICLR, and NeurIPS. He has chaired or co-organized workshops on security and privacy for machine learning at ICML, DSN, and NeurIPS.

About The Schwartz Reisman Institute for Technology and Society

The Schwartz Reisman Institute for Technology and Society (SRI) is a research and solutions hub at the University of Toronto dedicated to deepening understanding of technologies, societies, and what it means to be human.

SRI integrates research across traditional boundaries and builds practical, implementable solutions that really make a difference.