Master of Science at Ā UniversitĆ© Laval Canada
John Doe, an Industrial Engineer, holds an MSc from UniversitĆ© Laval (2024) and a BSc from K. N. Toosi University of Technology (2017). Currently a Logistics Analyst at InnovLog in Montreal, QC š¦. 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 š. 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 š.
profile
Education:
- MSc in Industrial Engineering, UniversitĆ© Laval, QC, Canada, 2021 ā Jan 2024
- BSc in Industrial Engineering, K. N. Toosi University of Technology, 2013 ā 2017
Professional Experience:
- Logistics Analyst, InnovLog, Montreal, QC, Canada, Apr 2024 – Present
- Research Assistant, Cirrelt, QC, Canada, 2021 ā 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
Publication
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 š (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) š
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, 1ā13 (2024) š²
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) š ļø