About Me (Bio)

Reza Samavi is currently an associate professor in the Department of Electrical, Computer, and Biomedical Engineering, Faculty of Engineering at Toronto Metropolitan University and a faculty affiliate with the Vector Institute for Artificial Intelligence. Reza received his PhD from University of Toronto and his research interests include Data Security & Privacy, Safety & Security of Machine Learning models, and Trustworthy AI. For his research on AI and Security, Reza has received several research grants from NSERC, SOSCIP, MITACS, HHS, IDEaS. For his research on information privacy he has received the Privacy Technologies Research Award from IBM and the Privacy By Design Research Award from the Information and Privacy Commissioner of Ontario.

I seek to recruit highly qualified individuals pursuing a graduate degree and a postdoc. I primarily supervise theoretical research on trust in machine learning, with emphasis on robustness. If your primary interest is purely applied work, please do not email. Competitive applicants should (i) identify a theoretical question aligned with our group’s topics—e.g., robustness–accuracy trade-offs, information-theoretic bounds under shift, certified robustness radii, or distributionally robust objectives—and write ≤1 page outlining the problem, assumptions, and the technical tools they plan to use; and (ii) map that theory to a target application (clinical or otherwise) in an additional ≤1 page, explaining how the analysis or guarantees would improve reliability in practice. When you are ready, attach your CV, complete transcripts (undergrad + graduate), and English-proficiency evidence (if applicable), and use the email subject format “Prospective Student: (your name) (the degree, e.g., MSc/MEng/PhD/PDF).” Everything should be sent as one or more attachments to your email and not as URLs. Due to the volume of emails only potential candidates will be contacted.

If you are currently an MEng student in our department and interested in completing a project at the intersection of Security and Machine Learning, I might be able to help you explore topics and projects that would suit your background and supervise your project. Your best chance to get involved would be taking EE8227: Secure Machine Learning course.