Hsinchu, Hsinchu City, Taiwan
- Conducted research in the field of natural language processing (NLP), with a specific focus on emotion and mental health-related topics, and utilized advanced NLP tools and techniques, such as sentiment analysis, topic modeling, and deep learning models, to extract valuable insights from unstructured text data.
- Proficient in programming languages like Python and relevant NLP libraries (e.g., NLTK, spaCy, TensorFlow) for research and data analysis.
- Collaborated on the project titled "Context-Aware Tweet Clustering and Contrastive Learning for Low Self-Esteem Analysis," which involved the development of novel NLP techniques for analyzing low self-esteem in social media posts.
- Co-authored research papers, including "Stress-coping Tweets Acquisition: A Two-phase Bootstrapping Method on Patterns and Semantic Features," which were successfully published in the International Conference on Technologies and Applications of Artificial Intelligence (TAAI).