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Mr Amirhossein Kazemisaboor | Engineering | Best Researcher Award 

Master of Science at  Université Laval Canada

John Doe, an Industrial Engineer, holds an MSc from Université Laval (2024) and a BSc from K. N. Toosi University of Technology (2017). Currently a Logistics Analyst at InnovLog in Montreal, QC 📦. His expertise includes optimizing logistics operations through data-driven insights and digital transformations. Previously, at Cirrelt and Mega Motor Company, John conducted impactful research and led process improvements 📊. He is skilled in Python, Power BI, and ERP/WMS/TMS integration, contributing to efficiency and innovation in supply chain management. John also instructs on optimization and data analysis at universities, enhancing educational initiatives 🎓.



  • MSc in Industrial Engineering, Université Laval, QC, Canada, 2021 – Jan 2024
  • BSc in Industrial Engineering, K. N. Toosi University of Technology, 2013 – 2017

Professional Experience:

  • Logistics Analyst, InnovLog, Montreal, QC, Canada, Apr 2024 – Present
  • Research Assistant, Cirrelt, QC, Canada, 2021 – Feb 2024
  • Industrial Engineer, Mega Motor Company, 2017 – 2021
  • Process Analyst, Mega Motor Company, 2016 – 2017

Training and Workshops:

  • Machine Learning Masterclass, Udemy, 2019
  • Python Bootcamp in Python 3, Udemy, 2018
  • Optimization in Python using GurobiPy and Docplex, Optimyar, 2018
  • Power BI for data analysis and BI implementation, Faradars, 2016
  • AnyLogic Software and Simulation Modeling, Shabih Pardazan, 2014
  • Microsoft Project Training, Parseh, 2013
  • PMBOK (Project Management Body of Knowledge), Parseh, 2013
  • Earned Value Management, Parseh, 2013


A simulation-based optimisation framework for process plan generation in reconfigurable manufacturing systems (RMSs) in an uncertain environment by A Kazemisaboor et al., International Journal of Production Research 60 (7), 2067-2085 📊 (2022)


A production bounce-back approach in the Cloud manufacturing network: case study of COVID-19 pandemic by E Shahab et al., International Journal of Management Science and Engineering Management 18 (4), 1 (2023) 🌐


Solution approaches to reduce problems with unbalanced supply and demand in transportation and harvest planning by A Kazemisaboor et al., International Journal of Forest Engineering, 1–13 (2024) 🌲


A novel service composition model considering the role of resilience in cloud supply networks by E Shahab et al., 6th International Conference on Industrial and Systems Engineering (ICISE) (2020) 🛠️


Amirhossein Kazemisaboor | Engineering | Best Researcher Award

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