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About

Najla Fattouch is a rising researcher at the intersection of artificial intelligence, the Internet of Robotic Things (IoRT), and smart agriculture. Her work focuses on making intelligent systems more transparent and efficient, with a particular emphasis on explainable AI and context-aware automation. In her highly cited 2025 systematic literature review, "Ontologies for Smart Agriculture: A Path Toward Explainable AI," she addresses the critical challenge of data opacity in agricultural AI systems, proposing ontological frameworks to enhance interpretability. This work has already garnered 8 citations, signaling its timely impact. Fattouch has also made significant contributions to IoRT-aware business processes, developing a meta-modeling approach (2022, 5 citations) and pioneering a decentralized multi-agent reinforcement learning method for context-aware resource allocation (2024, 4 citations). Her decision-making framework for IoRT-aware business process outsourcing (2022, 3 citations) further demonstrates her ability to tackle real-world industrial challenges. Through her model-based approaches for transformation and verification, Fattouch is shaping the future of autonomous, explainable systems in both agriculture and Industry 4.0.