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Chair holder

As Canada Excellence Research Chair in Data Science for Real-Time Decision-Making at Polytechnique Montréal, Dr. Andrea Lodi holds Canada’s main chair in Operations Research. The Chair’s mission is to combine knowledge acquisition through Machine Learning with decision making through Mathematical Optimization in a unified approach that is able to take advantage of the virtually unlimited quantity of data and lead to Data-Driven Innovation.

What is the Chair about?

The Canada Excellence Research Chair in Data Science for Real-Time Decision-Making aims at developing new tools and methodologies that will allow enormous volumes of data from multiple sources to be processed and analyzed in real time — in order to obtain usable knowledge and to automate decision-making. By combining processes for analyzing highly targeted data and real-time decision-making, their mathematical model-based tools will help organizations improve performance, by creating highly customized outputs and taking into account the environments, needs and individual behaviors of their clients or users. The applications that result will foster new business models that are based on accurate depictions of user behaviors and expectations, combined with competitors’ responses. The many sectors that could benefit include transportation management, energy, health care and manufacturing, as well as supply chain management and logistics.

The Chair will make it possible to train the next generation of data science specialists, who will be able to master the scientific, technological and economic issues emerging from the big-data explosion. Their multidisciplinary skills and their understanding of business issues will make them a labor force highly sought-after by employers from every sector of the economy who wish to transform their decision-making processes.

Software development project

The research activities within the Chair has been consolidated through the development of Ecole standing for Extensible Combinatorial Optimization Learning Environments and aiming to expose a number of control problems arising in combinatorial optimization solvers as Markov Decision Processes. Rather than trying to predict solutions to combinatorial optimization problems directly, the philosophy behind Ecole is to work in cooperation with the state-of-the-art Mixed Integer Linear Programming solver SCIP that acts as a controllable algorithm.

More information


Special Job Market DOTs Session this Friday, December 4 at *2pm ET* #DiscreteOptTalks!

Join us for 3 exciting 20-min talks+discussion after with:

Alfredo Torrico, Postdoc at @DS4DM
Cheng Guo @chengg04, PhD student at @uoftmie
David Bernal @bernalde, PhD student at @CMU_ChemE


@69alodi @Khalid_Montreal Thank you @Khalid_Montreal and @69alodi, for your support, guidance, and friendship. It was the best postdoc one could hope for, and I appreciate having the opportunity to learn from the collaborative, inquisitive, energetic, diverse, and cross-disciplinary skilled @DS4DM team.

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October 2, 2020: Mathieu Tanneau‘s defends his thesis on Exploiting structure in Mixed-Integer Linear and Non-Linear Programming

October 2, 2020: Members of the Chair, Elias Khalil and Aleksandr Kazachkov are hosting a session of Discrete Optimization Talks, featuring Andrea Lodi and Tuomas Sandholm. Details are up on the website:

October 1, 8, 15, 22, 29 2020: This first-ever edition of IVADO Digital October will showcase student-led research in our IVADO community. All month long, digital intelligence will be front and centre, starting with a distinguished panel of experts on October 1 including Prof. Andrea Lodi and followed by presentations of multidisciplinary projects by our scholarship recipients.


The Chair relies on various public and private partners in hospitals and industrial sectors to play an active role in technological, economic and social development.

About the CERC program