CV

Education

• Ph.D in Computer Scinenc, University of Waterloo, Waterloo, Canada, 2021

Research and Work experience

• 2024 - Present:
  • Applied ML Scientist at the Vector Institute
  • Overview: I continue my work on privacy preserving maching learning for applications in various industry sectors
• 2023 - 2024:
  • Postdoctoral Researcher at the Vector Institute
  • Overview: At Vector, I worked on privacy preserving maching learning for applications in various industry sectors
• 2021 - 2023:
  • Senior cryptography consultant at RBC (Royal Bank of Canada)
  • Overview: At RBC, I lead preparation for post-quantum cryptography migration, consulted with technology groups and conducted research to identify options that meet their security requirements, and developed cryptographic architectural patterns and standards in the organization.
• Fall 2020:
  • Research Intern, National Research Council (Canada)
  • Overview: I am working on designing a secure mechanism to perform join operation over encrypted data. Our work enables the data owner to outsource performing operations on his/her data while keeping the data private.
• Summer 2020:
  • Research Intern, Microsoft Research (US)
  • Overview: Machine learned models trained on organizational communication data, such as emails in an enterprise, carry unique risks of breaching confidentiality. My project at MSR shows how confidentiality relates to privacy in an enterprise context, and designs a model to preserve confidentiality for correlated data while leveraging principles from differential privacy.
• 2018-2021:
  • Research and Teaching Assistant, University of Waterloo, Canada
  • Overview: I conducted several projects during my PhD program focusing on security and privacy in data management and machine learning, namely on: i) differential privacy, ii) multi-party computation, and iii) watermarking in neural networks.