Marc-Etienne Brunet

Marc-Etienne is an Applied Research Scientist and Research Lead working on the security of AI systems with a focus on risk evaluation and adversarial testing.

He has helped develop SOPs for high-risk AI, published work on interpretability and algorithmic bias at top academic conferences, patented an explainability method and applied it in customer engagements, as well as advised an international financial regulator on operationalizing machine learning fairness principles.

He has a Masters and PhD from the University of Toronto (Vector Institute), where he focused on machine learning interpretability under the supervision of Richard Zemel and Ashton Anderson. He also has a Bachelor’s in electrical engineering from McGill University in Montreal.

Previously, he was co-founder and CTO of Neo Smart Blinds, an Internet of Things (IoT) startup now selling its products and services globally. He has also worked as a consultant in IoT and predictive analytics.