Research
Research at the intersection of natural language processing, large language models, healthcare, sentiment and emotion, and information retrieval.
Language Intelligence
I study methods for language understanding and generation, including representation learning, multilingual modeling, structured prediction, and adaptation of large language models to domain-specific tasks.
Human-Centered AI
My medical NLP research explores how language technologies can support healthcare information access and understanding, including healthcare named entity recognition, medical question answering, mental-health text analysis, and clinical decision support.
Affective Computing
I investigate fine-grained affective representations beyond categorical polarity, with emphasis on valence–arousal modeling, dimensional sentiment resources, aspect-based sentiment analysis, and multilingual emotion understanding.
Search & Retrieval
I work on semantic retrieval and ranking methods for finding relevant information from large collections, including dense retrieval, neural reranking, semantic similarity, and retrieval-augmented language applications.
Research Resources
Multilingual and multidomain resources for dimensional aspect-based sentiment analysis.
Dataset & project →Valence–arousal resources for Chinese dimensional sentiment analysis.
Dataset →A Chinese healthcare named entity recognition corpus for medical language understanding.
Dataset →Publications
Journal articles, conference papers, and preprints are maintained on the Publications page.