I'm an Associate Professor in the Department of Computing Science and a PI at Amii.
Before joining the University of Alberta in February 2020, I spent many years in industry research working on many interesting problems. Most recently I was a research team lead at Borealis AI (a research institute for the Royal Bank of Canada), where my team worked on privacy-preserving methods for machine learning models and other applications for the bank. Prior to that I spent many years in research labs such as Bell Labs, Technicolor, and Orange.
Please see here for more details.
My research interests are in probabilistic modelling and algorithmic design of machine learning for networked and multi-agent systems, and inference under bias and privacy constraints.
My current focus is on privacy, and fairness and bias in machine learning.
An introduction to the tools of set theory, logic, and induction, and their use in the practice of reasoning about algorithms and programs. Basic set theory; the notion of a function; counting; propositional and predicate logic and their proof systems; inductive definitions and proofs by induction; program specification and correctness. Prerequisites: Any 100-level CMPUT course, CMPUT 274 or SCI 100.Winter Term 2021