Principal Investigator
Prof. Nicolas Papernot
Nicolas is an Assistant Professor in the Department of Electrical and Computer Engineering and the Department of Computer Science at the University of Toronto. He is also a faculty member at the Vector Institute where he holds a Canada CIFAR AI Chair.
nicolas.papernot@utoronto.ca
https://www.papernot.fr
Current Members
Adam Dziedzic
Postdoctoral Fellow
Applied ML, Trustworthy ML, Robustness, Adversarial ML, ML in Healthcare, Data Science, Data Privacy, Applied Differential Privacy, FFT, Databases
Muhammad Ahmad Kaleem
Engineering Science student
Robustness, Differential Privacy, Self-supervised Learning, Model Extraction
Anvith Thudi
Mathematics Specialist Undergraduate student
Robustness, Adversarial Attacks, Unlearning, Verifiable-Learning
Hongyu (Charlie) Chen
Engineering Science student
Model Compression, AutoML, Out-Of-Distribution Detection, Information Theory
Emmy Fang
MS student
Privacy-Preserving Machine Learning, Collaborative Training, Natural Language Processing, Applications of ML in Healthcare
Franziska Boenisch
Research Intern
Privacy of ML, Robustness of ML, Differential Privacy, Privacy Attacks against ML, Data Anonymization, Privacy of Synthetic Data
Jiaqi Wang
MASc student
Differential Privacy, Collective Decision Making, Property Inference, Reinforcement Learning
Jonas Guan
PhD student
Robustness, Causality, Reinforcement Learning, Artificial General Intelligence, Malware Analysis
Mohammad Yaghini
PhD student
Trustworthy ML, Intellectual Property of ML, Algorithmic Fairness, ML Safety in Audio Domain, Game Theory and Mechanism Design
Natalie Dullerud
MS student
Forms of Bias, Fairness, Verification, ML in Healthcare, DP Theory, Metric Learning, Adversarial Robustness, Empathy in RL
Nick Jia
PhD student
Robustness, Unlearning, Generative Models, Reinforcement Learning, DNN as Intellectual Property
Stephan Rabanser
PhD student
Robustness, Safety, Causality, Reliability, Uncertainty Quantification, Distribution Shifts, Generative Models, Anomaly Detection