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About

Hans Aoyang Zhou is an emerging researcher at the intersection of artificial intelligence and advanced manufacturing, with a focus on applying cutting-edge machine learning techniques to real-world industrial challenges. His work spans deep reinforcement learning for robotics, actionable AI frameworks for Industry 4.0, and large language model (LLM) applications in production environments. Zhou's most recognized contribution is his reward curriculum approach to deep reinforcement learning for high-dexterity robotic assembly tasks, a paper that has garnered 14 combined citations across its versions and addresses one of manufacturing automation's most persistent bottlenecks: flexible, intelligent robotic control without traditional programming constraints. His research on the Internet of Production (IoP) further explores how actionable AI can bridge inter-company communication gaps, enhance human-robot collaboration safety, and advance IIoT integration under Industry 4.0 paradigms. More recently, Zhou has turned his attention to LLM-based copilot systems for manufacturing equipment selection, demonstrating a forward-looking interest in harnessing generative AI to support complex industrial decision-making. With a growing citation record and research spanning robotics, smart manufacturing, and applied AI, Zhou represents a promising voice in the future of intelligent production systems.