If you want to know what they have worked on in the past and how they could help you, come and meet them. In person or via videoconference (link will be provided to those who register)

This activity is intended for regular members of GERAD (professors and research associates)

Ahmed Beljadid works as a research assistant in data science/operational research at GERAD. As an operational research analyst at GERAD, he has recently worked on:

• Route planning for Revenu Québec inspectors.
  
• DLP planning (Phase 3-4) for OCP Morocco.
  
• Refit Optimizer for Thales Canada.
  
• Lagrangian decomposition for a strategic mine planning project for Rio Tinto.
  
• Hospital Optimizer for Thales Canada.
  

In addition to his knowledge of operational research and data science, Ahmed has 20 years of experience in C/C++ programming, 15 years in operational research (exact and heuristic methods), 8 years in SQL programming (Microsoft, PostgreSQL, and SQLite), and 3 years of experience in system administration (Unix, Microsoft, and MacOS). Ahmed would be able to help you and your teams with industrial projects where solutions (integration) are expected. Through his supervision, he can help your students deliver higher-quality code and, if necessary, rewrite the code according to the client's specifications (or integrate it). He can support the transition for collaborative and multi-phase projects, so that new students can continue the work already accomplished by the team.

Patrick Munroe has been working as a research officer in data science/operations research at GERAD since November 2021. Prior to that, he was a postdoctoral fellow at Polytechnique Montréal under the supervision of François Soumis and Guy Desaulniers. During his time at GERAD, Patrick has worked on numerous projects related to operations research and data science, including:

• The design of integer linear optimization models and stochastic models for air cargo delivery planning.
  
• The development of heuristics for optimizing staff shift scheduling.
  
• The creation of statistical and machine learning models to forecast demand for e-commerce air delivery.
  
• The development, in Python, of a multimodal public transit simulator.
  
• The addition of new cutting planes to an integer linear optimization model applied to mine planning.
  
• The design of new strategies in a large neighborhood search algorithm for mine planning.
  
• The development, in C++ and Python, of a solver for the resource-constrained shortest path problem.
  

In addition to his background in operations research and data science, Patrick has many years of programming experience in various languages, including C++, Python, Java, C#, and PHP. Patrick is well equipped to provide support both in general software development and in the design, implementation, and testing of optimization and machine learning algorithms or models.