Ah-Lian Kor

Papers

Total Citations

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About

Ah-Lian Kor is a researcher at the forefront of affective computing and human-robot interaction (HRI), with a particular focus on modeling and simulating human emotional states. Her work bridges artificial intelligence, fuzzy logic, and multi-modal data analysis to create more natural and responsive robotic systems. Kor’s most-cited paper, “Personalized emotion analysis based on fuzzy multi-modal transformer model” (2024, 7 citations), introduces a novel framework that integrates fuzzy logic with transformer architectures to capture the nuanced, personalized nature of human emotions. This work addresses a critical gap in emotion recognition by moving beyond one-size-fits-all models. In her second major contribution, “The Emotional State Transition Model Empowered by Genetic Hybridization Technology on Human–Robot Interaction” (2024, 2 citations), Kor tackles the challenge of simulating realistic emotional transitions in robots, using genetic algorithms to evolve more adaptive and lifelike emotional responses. Her earlier work on “Qualitative Spatial Reasoning for Orientation Relations in a 3-D Context” (2018, 2 citations) demonstrates a foundational expertise in spatial reasoning, which informs her current HRI research. Kor’s innovative combination of fuzzy systems, deep learning, and bio-inspired algorithms positions her as a rising voice in creating emotionally intelligent robots that can genuinely understand and mirror human affect.