Université de Montréal


Data Serving Canadians: Deep Learning and Optimization for the Knowledge Revolution

Data-driven innovation (DDI) is a key enabler of future growth and well-being for Canadians. With data being generated and collected at ever-increasing rates, we have entered a big data era that offers tremendous opportunities for new discoveries, technologies, processes and products that will change our lives and definitely propel us into a true knowledge-based society.

Campus Montréal, the alliance of the Université de Montréal, Polytechnique Montréal and HEC Montréal, is proposing a transformative and far-reaching strategy that capitalizes on the unique and synergistic combination of machine learning / deep learning and operations research—the science of optimization. Deep learning, largely pioneered and developed on campus, provides computers with quasi-human-level performance in, e.g., computer vision and speech recognition.

The strategy, which lies at the core of data-driven innovation, will pave the way to major scientific breakthroughs, allowing useful information to be efficiently extracted from massive data sets (machine learning) and turned into actionable decisions (operations). The transformative potential of the data-science research will be fully realized through the development of applications in sectors that present major opportunities for value creation in which Campus Montréal is already a recognized leader and works closely with well-established partners from the public and private sectors. These include human health, transportation and logistics, commerce and information services, and energy networks.

This strategy, firmly embracing the three pillars of the Canadian government’s science, technology and innovation strategy—people, knowledge and innovation—will be spearheaded by the flagship Institute for Data Valorization, whose mission is to expand fundamental and multidisciplinary research in data science, and turn scientific discoveries into marketplace applications, industry partnerships, and spin-offs. The strategy will contribute to training a knowledgeable workforce of data scientists with entrepreneurial skills—which will be critical for Canada to reap the economic and societal benefits of data-driven innovation.