Max Robotics — Global Service Robot Directory + US Certification

About

Mingnan Luo is a leading researcher in human-robot interaction, specializing in the development of socially intelligent robots that can perceive and respond to human engagement. Her core research areas include interpretable machine learning, fuzzy inference systems, and visual feature analysis for social robotics. Luo’s major contribution is pioneering methods for recognizing the intensity of human engagement intention (IHEI), enabling robots to distinguish primary interaction partners in multi-person scenarios. Her most cited work, "A method based on interpretable machine learning for recognizing the intensity of human engagement intention" (2023, 7 citations), introduces a transparent AI framework that allows robots to "perceive" human social cues with greater precision. This is complemented by her "Two states fusion fuzzy inference system" (2023, 5 citations) and her foundational "Interactive Intention Prediction Model" (2021, 4 citations), which together form a robust toolkit for humanoid robots to navigate complex social environments. Luo’s work is critical for advancing natural, human-like interaction capabilities in service and companion robots, directly addressing the challenge of making machines socially aware. Her research has significant implications for assistive technology, collaborative manufacturing, and everyday human-robot coexistence.