Alexandre is a Research Scientist at ServiceNow Research. His main interests revolve around multi-task transfer learning using probabilistic machine learning, causality and meta-learning. In his free time, he explores how AI can help solve climate change issues.
Alexandre joined Element AI in the early 2017 as its first Research Scientist. Prior to Element AI, he worked 3 years at Google in the Research Group for building end-to-end question answering systems using deep learning. This system is currently in use by Google’s search engine to answer some of the most complex questions.
He obtained his PhD in theoretical machine learning, working with Mario Marchand and Francois Laviolette, during which he developed bridges between Bayes and PAC-Bayes theories. He obtained his Master with Douglas Eck in the former MILA where he applied machine learning to music. Finally, he studied Physics during his undergrad.
Alexandre has been playing with neural networks in his early career, in the beginning of 2000, where he self-thought himself machine learning using Christopher Bishop’s first book. He applied his knowledge to solve computer vision problems in the production line of optical components at ITF technologies.