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Institute for Data Valorization (IVADO)

Institute for Data Valorization (IVADO)

IVADO is an advanced multidisciplinary center for professionals and researchers to develop resources and expertise in data science, operational research and artificial intelligence.

The Institute for Data Valorization (IVADO) is an advanced multidisciplinary center for industry professionals and academic researchers to develop synergy in resources and cutting-edge expertise in operational research, data science and artificial intelligence.

The institute was formed out of academic and industrial initiative as part of Campus Montréal, bringing together HEC Montréal, École Polytechnique de Montreal and Université de Montréal. IVADO's early members in the corporate sector are Hydro-Québec, CAE, Cogeco, Thales, National Bank of Canada and Gaz Métro. Members from the academic sector are the Group for Research in Decision Analysis (GERAD), the Inter-university Research Center on Enterprise Networks, Logistics and Transportation (CIRRELT), the Montreal Institute for Learning Algorithms (MILA), the Canada Excellence Research Chair in Data Science for Real-Time Decision-Making, the Department of Computer Sciences and Operations Research at Université de Montréal, the Department of Mathematics and Industrial Engineering at Polytechnique Montréal, Tech3Lab, the Centre de Recherches Mathématiques and the Department of Decision Sciences at HEC Montréal.

IVADO members supply data management methods and inform decision making for superior resource use. It creates opportunities for knowledge exchange and collaborations between the specialists, partners, researchers and students in its network. It is a center for knowledge in sectors including statistics, business intelligence, deep learning, applied mathematics, data mining and cybersecurity. The institute supports the development of processes to extract trends, metrics and concrete information from the jumble of big data.

IVADO aims to be the link between academic expertise and the business needs of organizations, from international corporations to start-ups. And contribute to the advancement of data science knowledge and train the next generations of data scientists.



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