ClosedPI: Dejing Dou
We propose to advance biomedical natural language processing by combining ontology-based reasoning, semantic search, and embedding-driven methods to improve information extraction, representation, and consistency detection in biomedical texts.
ActivePI: Nisansa de Silva
This project delves into the synergy between Natural Language Processing (NLP) and the legal domain, presenting novel solutions to enduring challenges.
ActivePI: Nisansa de Silva
We propose to advance automatic summarization and generation techniques, with a focus on aspect-aware methods that capture fine-grained information and sentiment within concise textual representations.
Conference Papers
K M Hewapathirana, Nisansa de Silva, C D Athuraliya, and Piumi Kandanaarachchi, "Domain Adaptation for Multi-document Summarisation: A Case Study in the Medical Research Domain", in Proceedings of the 39th Pacific Asia Conference on Language, Information and Computation, 2025, pp. 791--802.
Workshop Papers
Viraj Gamage, Menuka Warushavithana, Nisansa de Silva, Amal Shehan Perera, Gathika Ratnayaka, and Thejan Rupasinghe, "Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning", in Proceedings of the 9th workshop on computational approaches to subjectivity, sentiment and social media analysis, 2018, pp. 260-265. doi: 10.18653/v1/W18-6238
