Bsc Eng. (Hons) (Moratuwa)
Vihanga Jayawickrama is a lecturer on contract at the Department of Computer Science and Engineering, University of Moratuwa. She obtained her BSc (Hons) in Computer Science & Engineering from the same department in 2022. Her research interests include machine learning, data science, and natural language processing.
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.
