About
Joren Gijsbrechts is an Assistant Professor in the Department of Operations, Innovation and Data Sciences at Esade Business School, Ramon Llull University. His research focuses on data-driven decision making in Operations Management, particularly leveraging Machine Learning and Prescriptive Analytics to enhance inventory and transportation management. He holds a PhD from KU Leuven and prior industry experience in Supply Chain and Operations at Procter & Gamble. Gijsbrechts contributes to the Business Network Dynamics research group and collaborates on the BuNeD: Business Network Dynamics project funded by AGAUR (2022–2025). His work addresses real-world challenges such as dual-sourcing strategies, nonstationary demand forecasting, and perishable inventory optimization through advanced algorithms like Deep Reinforcement Learning.
Research interests include:
- Machine Learning applications in supply chains
- Data-driven inventory control systems
- Prescriptive analytics for operational decision making
Publications emphasize practical implementations of reinforcement learning frameworks to solve complex inventory problems (e.g., multi-echelon systems, lost sales scenarios) and supply chain reshoring strategies. His work has been cited over 460 times, reflecting impactful contributions to operational efficiency.
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