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: Nisansa de Silva
This project delves into the synergy between Natural Language Processing (NLP) and the legal domain, presenting novel solutions to enduring challenges.
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.
Conference Papers
Gihan Weeraprameshwara, Vihanga Jayawickrama, Nisansa de Silva, and Yudhanjaya Wijeratne, "Sinhala Sentence Embedding: A Two-Tiered Structure for Low-Resource Languages", in Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation, 2022, pp. 325--336. doi: 10.48550/ARXIV.2210.14472 
Sahan Jayasinghe, Lakith Rambukkanage, Ashan Silva, Nisansa de Silva, and Amal Shehan Perera, "Critical Sentence Identification in Legal Cases Using Multi-Class Classification", in 2021 IEEE 16th International Conference on Industrial and Information Systems (ICIIS), 2021, pp. 146--151. doi: 10.1109/ICIIS53135.2021.9660657
