Assia Bakali

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About

Assia Bakali is a prominent researcher whose work lies at the intersection of neutrosophic graph theory and its applications in robotics and artificial intelligence. Her most-cited paper, "Trends on Extension and Applications of Neutrosophic Graphs to Robots" (2021), has garnered 2 citations, reflecting her pioneering efforts to extend classical graph structures into neutrosophic frameworks—a mathematical tool that handles uncertainty, indeterminacy, and inconsistency in complex systems. Bakali’s major contributions include developing novel models that integrate neutrosophic sets with graph theory, enabling more robust decision-making and path-planning algorithms for autonomous robots. By addressing real-world ambiguities in sensor data and environmental interactions, her work has laid a foundation for smarter, more adaptive robotic systems. Beyond this flagship study, she has explored the theoretical underpinnings of neutrosophic graphs, advancing their formal properties and expanding their applicability to fields like network analysis and optimization. Bakali’s research is notable for bridging abstract mathematics with practical engineering challenges, offering tools that enhance reliability in uncertain environments. Her growing citation record underscores her emerging influence, making her a key voice in the evolving dialogue between neutrosophic logic and intelligent systems.