Remco Dijkman

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About

Remco Dijkman is a leading researcher at the intersection of business process management, artificial intelligence, and operations research. His work focuses on developing intelligent systems that optimize complex decision-making in manufacturing and supply chain contexts. A standout contribution is his pioneering application of Deep Reinforcement Learning (DRL) to inventory control, as detailed in his highly cited 2025 paper "Deep Controlled Learning for Inventory Control" (20 citations). This work addresses the critical gap between generic DRL algorithms and the unique demands of inventory management, proposing tailored learning frameworks that significantly improve efficiency and adaptability. Dijkman also advances process execution support for high-tech manufacturing, as seen in his 2019 paper (10 citations), where he designs systems to handle the intricate, real-time constraints of production environments. His research bridges theoretical AI advancements with practical industrial applications, earning recognition for its impact on both academic literature and operational practice. Through these contributions, Dijkman is shaping the future of autonomous decision-making in logistics and manufacturing.