Yue Zhan

Papers

Total Citations

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About

Yue Zhan is a researcher at the intersection of human-robot interaction and natural language programming, with a focus on making robotics education accessible to novice programmers. Their major contribution lies in developing controlled natural language (CNL) systems that allow users to program robots—specifically the Lego Mindstorms EV3—using intuitive, high-level language rather than traditional code. Zhan’s 2018 paper introduced a CNL-based program synthesis system designed to help middle and high school students and non-programmers learn programming through robotics, a work that has garnered 6 citations for its educational impact. Building on this, their 2021 paper, with 11 citations, breaks down complex robot path-finding abstractions into natural language commands, further lowering barriers to entry in robotics. Zhan’s work is notable for bridging the gap between abstract computational thinking and practical, hands-on learning, empowering a new generation of young roboticists. Their research continues to influence educational robotics by demonstrating how natural language can democratize programming skills.