ActivePI: 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.
ClosedPI: Rohan Samarajiva
We propose to investigate the role of natural language processing in government by building methods, frameworks, and resources that enable data-driven policy-making while ensuring ethical, transparent, and inclusive outcomes.
ActivePI: 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.
ActivePI: 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.
White Papers
Yudhanjaya Wijeratne, Nisansa de Silva, and Yashothara Shanmugarajah, "Natural Language Processing for Government: Problems and Potential", LIRNEasia, 2019. doi: 10.13140/RG.2.2.34297.31845
Preprints
Nisansa de Silva, Danaja Maldeniya, and Chamilka Wijeratne, "Subject Specific Stream Classification Preprocessing Algorithm for Twitter Data Stream", arXiv preprint arXiv:1705.09995, 2017. doi: 10.48550/ARXIV.1705.09995
