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About

Pengzhong Li is a leading researcher in advanced manufacturing and human–robot collaboration (HRC), with a focus on creating safer, more efficient, and human-centric assembly systems. His work bridges the gap between automation and human skill, developing intelligent frameworks that optimize task allocation, motion prediction, and quality control in collaborative environments. Li’s most cited paper, “Safety-efficiency integrated assembly: The next-stage adaptive task allocation and planning framework for human–robot collaboration” (2025, 17 citations), introduces a pioneering approach that balances productivity with worker safety—a critical challenge in modern manufacturing. He also developed a performance loss model for predicting robot assembly quality (2009, 3 citations), offering a systematic method to quantify how assembly errors degrade robot performance over time. More recently, Li has advanced human-centric planning through reinforcement self-learning multi-objective evolutionary optimizers (2025, 2 citations) and accurate human motion prediction algorithms (2024, 2 citations), enabling real-time, adaptive HRC. His work is instrumental in shaping the next generation of resilient, sustainable, and human-aware manufacturing systems.