Clément Canonne is a Senior Lecturer in the School of Computer Science of the University of Sydney. Prior to that, he was a postdoc first in the Stanford Theory Group, then at IBM Research Almaden. Even prior to that, he obtained his PhD from the Computer Science department of Columbia University, where he was advised by Prof. Rocco Servedio. Long ago, in a distant land, he received a MSc in Computer Science from the Parisian Master of Research in Computer Science, and an engineering degree from one of France's "Grand Schools," the École Centrale Paris.
His main areas of study are distribution testing (and, broadly speaking, property testing), learning theory, and, more generally, randomized algorithms and the theory of machine learning. One of his focuses is on understanding the computational aspects of learning and statistical inference subject to various resource or information constraints. Another, not quite disjoint from the first, lies in reliable and rigorous approaches to data privacy, specifically differential privacy.