Yu-i Ha

Korea Advanced Institute of Science and Technology

Papers

Total Citations

H-Index

About

Yu-i Ha is a researcher at the forefront of affective computing and natural language processing, with a focus on advancing emotion recognition in artificial intelligence. Her most-cited work, "Detecting Multiclass Emotions from Labeled Movie Scripts" (2018, 5 citations), tackles a critical challenge in AI: the nuanced detection of complex negative emotions like anger and sadness. While conventional sentiment analysis tools often rely on binary classifications, Ha’s research demonstrates the necessity of multiclass emotion detection for developing AI systems capable of delicate, context-aware responses—an essential step toward empathetic human-machine interaction. By leveraging labeled movie scripts as a rich training resource, she has contributed to bridging the gap between simplistic sentiment polarity and the subtlety of real-world emotional expression. Though early in her career, Ha’s work signals a promising trajectory in making AI more emotionally intelligent, addressing a key limitation in current systems. Her contributions are particularly relevant for researchers in human-computer interaction and affective computing, offering a foundation for more responsive and socially aware AI technologies.