I arrived in Montréal in 2015, and what I have found here in Québec is a highly stimulating environment where collaboration among strong academic institutions is not only encouraged, but rather is recognized as a means to a successful career.

This has undoubtedly been a key factor that explains the creation of what many in the world refer to now as the Montréal AI Ecosystem, where academia and industry profitably interact, transferring the most advanced AI research into applications. Once again, from a science and technology perspective, this is powered by another close collaboration between researchers in two different disciplines: machine learning and discrete optimization.

The aforementioned unique collaborative approach to research is one of the ways in which the Montréal AI Ecosystem differs: the use of machine learning for knowledge acquisition, and the use of discrete optimization for optimal decision making. The above is an extremely effective mix that has proven successful in diverse industrial contexts such as logistics, healthcare, transportation, supply chains, and finance, just to name a few.

Andrea Lodi is Full Professor of Mathematical Optimization at Polytechnique Montréal, where he holds the Canada Excellence Research Chair in “Data Science for Real-time Decision-Making.” Professor Lodi is also Scientific Co-Director of IVADO, the Montréal Data Science Institute, and Co-Founder and Scientific Director of IVADO Labs.