Padmini Rajagopalan

Papers

Total Citations

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About

Padmini Rajagopalan’s research bridges artificial intelligence and manufacturing, with a focus on multiagent systems and neural network applications. Her most cited work, “Multiagent Learning through Neuroevolution” (2012, 13 citations), explores how evolutionary algorithms can train multiple autonomous agents to cooperate and adapt, offering insights into complex, decentralized problem-solving. Earlier, her influential review “Applications of Neural Network in Manufacturing” (1996, 8 citations) surveyed how neural models—inspired by the brain’s cognitive processes—can optimize manufacturing operations, from quality control to scheduling. This work helped establish neural networks as practical tools in industrial engineering, connecting psychological models of cognition to real-world production challenges. Though her citation counts are modest, Rajagopalan’s contributions are notable for their interdisciplinary reach, linking neuroevolution, multiagent learning, and manufacturing. Her research demonstrates how biologically inspired algorithms can solve practical engineering problems, making her work valuable for students and researchers interested in the intersection of AI, robotics, and industrial automation.