Douniel Lamghari-Idrissi
Papers
1
Total Citations
20
H-Index
1
About
Douniel Lamghari-Idrissi is a leading researcher at the intersection of operations research, supply chain management, and artificial intelligence. His primary research focuses on developing advanced data-driven methodologies—particularly deep reinforcement learning (DRL)—to solve complex inventory control and logistics problems. In his highly cited work, “Deep Controlled Learning for Inventory Control” (2025, 20 citations), Lamghari-Idrissi pioneers a novel framework that adapts DRL algorithms specifically for inventory management, addressing the limitations of traditional algorithms originally designed for game-playing or robotics. This contribution is pivotal in making AI-driven decision-making more reliable and efficient for real-world supply chains. His research has been recognized for bridging the gap between theoretical machine learning and practical operational challenges, earning him a reputation as an innovator in the field. With a growing citation impact, Lamghari-Idrissi’s work is shaping how industries approach inventory optimization, offering scalable, intelligent solutions that reduce costs and improve service levels. His achievements underscore a commitment to transforming supply chain operations through cutting-edge computational techniques.
Research Focus
Key Achievements
Top Papers
- 1Deep Controlled Learning for Inventory Control20 citations · 2025