Martin Cousineau is an assistant professor in the Department of Logistics and Operations Management at HEC Montréal and a professor of the Institute for Data Valorization (IVADO). He is a co-head researcher of the Sustainable Health research theme of the International Observatory on the Societal Impacts of AI and Digital Technology (OBVIA) and a member of the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT). He is specialized in methods at the intersection of operations research and artificial intelligence, with applications to logistics, transportation and healthcare.
Ph.D. in Management, 2020
McGill University
M.Sc. in Administration, 2013
HEC Montréal
B.Ing. in Mechanical Engineering, 2010
École Polytechnique de Montréal
As highlighted in Bengio et al. (2021), machine learning appears as a promising avenue to solve combinatorial optimization problems, directly or along operations research methods. My projects along this theme include:
Another somewhat related project is the use of constrained optimization for causal inference.
I also have several projects on demand forecasting, inventory management, supplier selection and scheduling. Some of which are more theoretical while others are more applied. Several of these logistics projects are related to the COVID-19 pandemic and thus are related to healthcare. Finally, I also have some pure healthcare projects, e.g., medical decision making for the management of treatment-resistant depression.
I teach the following courses at HEC Montréal.