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About
Prerna Garg is a researcher at the forefront of human-robot collaboration, specializing in context-aware robotic assistance and semantic digital twin technologies. Her work bridges artificial intelligence and robotics to create intelligent systems that can recognize human intentions and adapt their behavior in real-time, particularly in industrial and workplace settings. Garg’s most cited paper, “Context-Aware Robotic Assistance for Workers Using Intention Recognition and Semantic Digital Twin” (2025), introduces a novel framework that integrates digital twin models with intention recognition algorithms, enabling robots to anticipate worker actions and provide proactive, safe, and efficient support. This contribution is pivotal for advancing collaborative robotics in manufacturing and logistics, where seamless human-robot interaction is critical. Though early in her career, Garg’s work has already garnered attention for its practical implications in Industry 4.0, and she is recognized for pushing the boundaries of how robots understand and respond to human behavior. Her research promises to redefine workplace automation, making it more adaptive and human-centric.
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