Liu Yisi

Papers

Total Citations

H-Index

About

Dr. Liu Yisi is a pioneering researcher at the intersection of human-robot interaction and cognitive ergonomics, specializing in the objective evaluation of humanoid robot design through eye-tracking analytics. Her major contributions lie in developing novel, data-driven methodologies that leverage ocular metrics to assess user preferences and first impressions of robot appearances—a critical factor influencing successful human-robot collaboration. In her landmark 2024 study on "Autoencoder-enabled eye-tracking data analytics," she introduced a machine learning framework that decodes subconscious visual attention patterns, achieving 5 citations and setting a new standard for quantifying aesthetic and functional design preferences. Her foundational 2020 work on "Evaluation of Humanoid Robot Design Based on Global Eye-Tracking Metrics" (3 citations) established the first systematic approach to using gaze behavior as a proxy for user satisfaction, demonstrating that initial visual impressions profoundly impact interaction quality. By transforming subjective design evaluations into objective, quantifiable data, Dr. Liu’s research provides engineers and designers with actionable insights to create more intuitive and appealing robots. Her work bridges cognitive science and robotics, offering a scalable toolkit for user-centered design in the rapidly evolving field of social robotics.