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Saeide Jamshidpour Poshtahani

Saeide Jamshidpour Poshtahani

Email: s.jamshidpourposhtahani@qmul.ac.uk

Project title

Sustainable & Resilient Closed-Loop Supply Chain of Electric Vehicle Batteries

Project Description

The rapid growth of electric vehicles (EVs) has intensified the need for battery supply chains that are both environmentally sustainable and operationally resilient. This project addresses this challenge by integrating closed-loop supply chain modelling, hybrid production strategies, and network analysis of global EV suppliers and OEMs. It examines how used batteries can be efficiently remanufactured, recycled, or repurposed, while mapping the structural dependencies and vulnerabilities of the EV supply network. By linking material flows, supplier relationships, and recovery strategies, the research develops a novel framework that informs sustainable, robust, and strategically optimized EV battery supply chains in a complex global market.

Supervision

  • 1st Supervisor: Professor Brigitte Granville
  • 2nd Supervisor: Dr Guven Demirel
  • 3rd Supervisor: Professor Eun-Seok Kim

 

Biography

Saeide is a PhD researcher in Business and Management at Queen Mary University of London, School of Business and Management, within the Department of Business Analytics and Applied Economics. Her research focuses on developing sustainable and resilient closed-loop supply chains for electric vehicle batteries.

She holds an MSc in Industrial Engineering from Kharazmi University of Tehran, where her master’s thesis developed a bi-objective vendor-managed inventory model for green supply chains, applying stochastic programming and optimization techniques. She also earned her BSc in Industrial Engineering from the University of Science and Technology of Mazandaran, where her bachelor’s thesis introduced a bi-level interdiction median model that incorporated demand distribution and disruption severity in supply networks.

Building on a strong foundation in industrial engineering, operations research, and optimization, Saeide has advanced her research to address critical challenges in sustainability and supply chain resilience. She has extensive teaching experience across a diverse range of subjects, including supply chain management and analytics, operations research and management, strategic analysis, human resource management, new product development, firms and nations in the global economy, and marketing, in both the UK and Iran.

 

Centre and Group Membership

  • Member of a Centre for Globalisation Research (CGR)
  • Member of Production and Operations Management Society (POMS)

Teaching and Membership

  • Teaching Associate, School of Business and Management, Queen Mary University of London (2023–Present)
  • Advance HE Associate Fellow, awarded Certificate in Learning and Teaching in Higher Education (CILT) with Distinction, Queen Mary University of London
  • Member of Teaching Recognition Programme (TRP) Community, Queen Mary University of London

 

Areas and Expertise

  • Supply Chain Management & Logistics,
  • Supply Chain Network Design,
  • Supply Chain Resilience,
  • Mathematical Modelling & Optimisation,
  • Operations Research,
  • Transportation & Logistics Analytics,
  • Network Science

 

Publications

Journal Articles

  • Jamshidpour Poshtahani, S., & Pasandideh, S.H.R. (2020). Optimising a bi-objective vendor-managed inventory of multiproduct EPQ model for a green supply chain with stochastic constraints. Journal of Industrial and Systems Engineering, 13, pp. 1–34.

Conference Presentations

  • Jamshidpour Poshtahani, S., Granville, B., Demirel, G., & Kim, E.K. Sustainable Inventory Management for Electric Vehicle Batteries: A Closed-Loop Supply Chain Approach with Buyback Pricing:
    • POMS International Conference, Istanbul, Türkiye, 2024
    • UK-China Workshop on Sustainable Supply Chains, Queen Mary University of London, June 2025.
    • EURO Conference, Leeds, UK, June 2025
  • Jamshidpour Poshtahani, S., & Pasandideh, S.H.R. (2018). Modelling and optimizing a bi-objective vendor-managed inventory in a two-echelon supply chain with EPQ, green condition, stochastic programming, and discount policy. 11th International Conference of Iranian Operations Research, Kermanshah, Iran.

 

 

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