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About

Hankz Hankui Zhuo is a researcher whose work sits at the intersection of artificial intelligence planning, human-robot interaction, and natural language processing. He is perhaps best known for his foundational contributions to the concept of **plan explicability and predictability** in robot task planning — a research thread exploring how autonomous robots can construct and communicate goal-oriented plans in ways that are cognitively accessible and safe for human collaborators. His 2017 paper on this topic has garnered 135 citations, establishing him as a key voice in making AI-driven robotics more transparent and trustworthy in human-populated environments. Zhuo's work reflects a consistent concern with bridging the gap between machine autonomy and human understanding. His research on collaborative robots (cobots) extended these ideas into practical deployment scenarios, while his more recent explorations — including choreography planning for dancing robots and the integration of AI planning with large-scale language models — demonstrate a creative and expansive research vision. His 2022 work on combining explicit and tacit knowledge through NLP and planning speaks to growing challenges of explainability in modern AI systems. Across his career, Zhuo has made meaningful strides toward AI systems that are not only capable, but interpretable and human-centered.