Vince Guan


Vince joined the Computational Privacy Group as a PhD student in Oct 2022. His primary privacy related research interests include privacy attacks against aggregate location data, and synthetic data generation. He is also interested in the research areas of feature importance, AI fairness, and information theory.

Originally from Canada, Vince studied mathematics at the University of British Columbia for his Bachelor’s degree (BA with Major in Mathematics with Minor in Philosophy), where he developed a keen interest in probability theory. He then pursued a MSc in Mathematics, also at the University of British Columbia, where he was supervised by Dr. Juncheng Wei and Dr. Mathav Murugan. Vince studied a wide range of subjects during his Master’s degree, including probability theory, partial differential equations, convex optimization algorithms, and graphical models and causal inference. His Master’s thesis and principal research focus was on the classification of Helmholtz solutions to generalized Laplacian operators. Directly following the completion of his Master’s degree, Vince worked with his former classmate, PhD student Joseph Janssen, and his former professor, Dr. Elina Robeva, to develop a feature importance method for data explanation with causal guarantees.