Samuel Rosat
Manager - Optimization (OR/AI) and Software Development @ GIRO
Canada
Montreal
Information Technology & Services
Gestion d’équipe, CPLEX, Operations Research, Mathematical Modeling, Mathematical Programming, Linear Programming, Matlab, Simulations, Applied Mathematics, LaTeX, AMPL, Optimizations, Algorithms, Java, Crew Scheduling, First Aid, Modélisation mathématique, Recherche opérationnelle, Mathématiques appliquées, Optimisation
Experience

Manager - Optimization (OR/AI) and Software Development
Montréal, Québec, Canada
+ Manages 2 development teams: one of Data Scientists (OR/AI) and one of Software Developers + Steering committee member for GeoRoute (GIRO's product for postal operations optimization) + Involved in the initiation and coordination of academic partnerships for GIRO

Adjunct Professor in Applied Mathematics
Région de Montréal, Canada
Adjunct Professor in the Applied Mathematics department of Polytechnique Montreal. Participates in research projects with the academic teams and coordinates research projects together with full-time professors. Member of the jury of graduate students.

Manager - Data Science (OR)
Région de Montréal, Canada
* Manager of the core optimization team (5 Computer & OR Scientists); * Product Manager of the crew planning optimizers; * Aligns the R&D projects with the business strategy and participates in the design of algorithms and solutions; * Collaborates with cross-functional management to create new initiatives or improve existing processes to increase the impact of the team; * Communicates advanced scientific concept to upper management and key stakeholders, acts as a catalyst between cross-functional teams; * Main industrial partner for $1M+ research projects with academic partners; * Strong involvement in the definition of the division's strategy and vision; * Participates in the business development and represents the company within the scientific community (co-chairman of an AGIFORS study group);

Researcher & PhD Candidate
Montréal
* Large-scale optimization by integral simplex methods (PhD project) * I designed inovative methods for solving large-scale scheduling problems from the transport industry. I proposed a benchmark of realistic data set of aircrew sceduling instances to evaluate the performance of my methods. The software I developed outperforms state-of-the-art solvers on most industrial instances on previous benchmarks, as well as on the realistic one I designed. * Nurse scheduling * With two fellow students, I designed and implemented an algorithm for the nurse scheduling problem. Given operational constarints, resource requirements, and a collective agreement, our method creates a 2-months scehdule for a nursing service. Our implementation only makes use of free and open-source third-party software. Our team was runner-up winner in the second International Nurse Rostering Competition. * Car driver routing * With fellow students, I designed and implemented a routing tool for car drivers for the international optimization competition of the Mathematical Calculus Society. Our team won the competition. * Other responsibilities * Elected representative of students at the GERAD research center (over 400 MSc and PhD students), coordinator of research seminars, supervisor of graduate interns.

Visiting PhD Student
Bologne et alentours, Italie
* Cutting planes for the integral simplex * During this visiting time at the Department of Electrical, Electronic and Information Engineering, I worked on the integration of cutting plane techniques in the integral simplex algorithm under the supervision of Prof. Andrea Lodi. This collaboration led to two research papers.

Graduate intern
Région de la baie de San Francisco, États-Unis
* Online algorithm for the arterial traffic estimation * During this internship at the California Center for Innovative Transportation (CCIT), I worked on the Mobile Millennium project. I took part in the development of an online algorithm for solving the LASSO problem. We applied this method to arterial traffic estimation, water flows modelling and statistical analysis of news data. Supervisors : Prof. Alexandre Bayen and Dr. Aude Hofleitner.
Education
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