Bsc Eng. (Hons) (Moratuwa)
Computer Science is unique and stand out among other sciences because it changes rapidly. So the people who involved in this area should be versatile. That's what I am. A versatile person with a knack to learn new technologies and willing to be an innovator with the goal of making life easy for people with softwares.
Keywords: Natural Language Processing | Big Data | Sinhala | Machine Learning / Deep Learning |
Journal Papers
Vihanga Jayawickrama, Gihan Weeraprameshwara, Nisansa de Silva, and Yudhanjaya Wijeratne, "Facebook for Sentiment Analysis: Baseline Models to Predict Facebook Reactions of Sinhala Posts", The International Journal on Advances in ICT for Emerging Regions, vol. 15, no. 2, 2022. doi: 10.4038/icter.v15i2.7248
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 
Gihan Weeraprameshwara, Vihanga Jayawickrama, Nisansa de Silva, and Yudhanjaya Wijeratne, "Sentiment Analysis with Deep Learning Models: A Comparative Study on a Decade of Sinhala Language Facebook Data", in 2022 The 3rd International Conference on Artificial Intelligence in Electronics Engineering, Association for Computing Machinery, 2022, pp. 16-22. doi: 10.1145/3512826.3512829
Vihanga Jayawickrama, Gihan Weeraprameshwara, Nisansa de Silva, and Yudhanjaya Wijeratne, "Seeking Sinhala Sentiment: Predicting Facebook Reactions of Sinhala Posts", in 2021 21st International Conference on Advances in ICT for Emerging Regions (ICter), 2021, pp. 177-182. doi: 10.1109/ICter53630.2021.9774796 
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
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.
