PI: 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.
PI: Nisansa de Silva
The Knowledge Representation project investigates methods for structuring, aligning, and reasoning over knowledge extracted from language, with particular emphasis on low-resource settings, domain-specific semantics, and intelligent information access.
PI: Nisansa de Silva
We propose to advance natural language processing for low-resource settings by leveraging data augmentation, transfer learning, and model adaptation techniques to overcome the scarcity of annotated data and linguistic resources.
PI: Dejing Dou
We propose to advance methods for semantic oppositeness detection in natural language, focusing on embedding-based models and contextual representations to improve reasoning and error detection in text.
PI: Nisansa de Silva
We propose to build and analyze Sinhala language resources, datasets, and models to strengthen NLP research for this low-resource language, while connecting it to English and Tamil through bilingual lexicons, embeddings, and cross-lingual methods.
PI: Nisansa de Silva
We propose to advance social media text analysis by combining linguistic study, preprocessing, and deep learning models to better capture sentiment, structure, and meaning in informal, large-scale user-generated text.
Journal Papers
Krishan Chavinda, Pasan Kalansooriya, Thushalya Weerasuriya, Nisansa de Silva, Uthayasanker Thayasivam, Kogul Srikandabala, Kirishnni Prabagar, and Damminda Alahakoon, "An emotion aware context adaptive machine learning approach for detecting hate speech in social media", Neural Computing and Applications, vol. 38, no. 8, pp. 1433-3058, 2026. doi: 10.1007/s00521-026-12029-8
Conference Papers
Imalsha Puranegedara, Themira Chathumina, Nisal Ranathunga, Nisansa de Silva, Surangika Ranathunga, and Mokanarangan Thayaparan, "Utilizing Multilingual Encoders to Improve Large Language Models for Low-Resource Languages", in Moratuwa Engineering Research Conference (MERCon), 2025. doi: 10.1109/MERCon67903.2025.11216992 
Sadeep Gunathilaka and Nisansa de Silva, "Automatic Analysis of App Reviews Using LLMs", in Proceedings of the Conference on Agents and Artificial Intelligence, 2025, pp. 828-839. doi: 10.5220/0013375600003890
Nisansa de Silva and Dejing Dou, "Semantic Oppositeness Embedding Using an Autoencoder-based Learning Model", in Database and Expert Systems Applications, 2019, pp. 159--174. doi: 10.1007/978-3-030-27615-7_12
