Academic Staff
- HHB703, Hung Hom Bay Campus
- +852 2766 4590
- jinghang.gu@polyu.edu.hk
ORCID ID
SCOPUS IDBiography
Dr. Jinghang Gu holds a PhD in Computer Science and Technology from Soochow University. His research lies at the intersection of computational linguistics, natural language processing, data mining, and large language models (LLMs). His work primarily focuses on developing AI-driven methodologies for computational linguistics, with particular interests in sentiment analysis, information extraction, multilingual and multimodal learning, as well as applications in biomedical and healthcare domains.
Education and Academic Qualifications
- 2014 - 2018
PhD in Computer Science and Technology, Soochow University
Academic and Professional Experience
- 2019 - 2023
Postdoctoral Fellow in Computational Linguistics, The Hong Kong Polytechnic University - 2018 - 2019
Senior Natural Language Processing Engineer, Baidu Inc.
Teaching Areas
- Programming
- Computational Linguistics
Research Interests
Selected Publications
- Bao, X., Gu, J., Wang, Z., & Huang, C. R. (2026). Sentimental image generation with image quality assessment. Pattern Recognition, 177, 113269. https://doi.org/10.1016/j.patcog.2026.113269
- Bao, X., Gu, J., Wang, Z., Jiang, X., & Huang, C. R. (2025). Exploring Context-Free Opinion Grammar for Aspect-Based Sentiment Analysis. IEEE Transactions on Knowledge and Data Engineering, 38(2), 1070-1083. https://doi.org/10.1109/tkde.2025.3632628
- Bao, X., Wang, Z., Gu, J., & Huang, C. R. (2025, November). CalligraphicOCR for Chinese Calligraphy Recognition. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 4865-4877. https://doi.org/10.18653/v1/2025.emnlp-main.245
- Bao, X., Wang, Z., Gu, J., & Huang, C. R. (2025, July). Revisiting classical Chinese event extraction with ancient literature information. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 8440-8451. https://doi.org/10.18653/v1/2025.acl-long.414
- Gu, J., Chersoni, E., Wang, X., Huang, C. R., Qian, L., & Zhou, G. (2022). LitCovid ensemble learning for COVID-19 multi-label classification. Database, 2022. https://doi.org/10.1093/database/baac103
- Jan 2026 - Dec 2027
General Research Fund awarded for the project “Towards Trustworthy AI in Healthcare: In-depth Investigation and Mitigation of Hallucinations in Biomedical Large Language Models” (PI)
- Association for Computational Linguistics
- China Computer Federation
- Chinese Information Processing Society of China
