Pascale started as a Postdoctoral Research Fellow at the Vector Institute in October 2023, and is advised by Nicolas Papernot and Shai Ben-David. Pascale works on the theoretical foundations of trustworthy machine learning. Previously, they obtained a DPhil (PhD) at the University of Oxford under the supervision of James Worrell, Varun Kanade and Marta Kwiatkowska. Their thesis studied the sample complexity of robust learning under evasion (test-time) attacks. Prior to that, Pascale obtained their masters at McGill University’s Reasoning and Learning Lab and was supervised by Prakash Panangaden and Doina Precup.
- Learning Theory
- Trustworthy Machine Learning