SMPTE ST 2110 Compliant Scalable Architecture on FPGA for end to end Uncompressed Professional Video Transport Over IP Networks. - Nisal Ranasinghe; Ravindu Bangamuarachchi; Jayath Seneviratne; Achini Jayawardane; Ajith Pasqual; R. M. A. U. Senarath (ASAP, 2019)

Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications. - Nisal Ranasinghe; A. Ramanan; S. Fernando; Pathima Nusrath Hameed; Damayanthi Herath; Tamasha Malepathirana; Ponnuthurai N. Suganthan; M. Niranjan; Saman K. Halgamuge (CoRR, 2022)

GINN-LP: A Growing Interpretable Neural Network for Discovering Multivariate Laurent Polynomial Equations. - Nisal Ranasinghe; Damith A. Senanayake; Sachith Seneviratne; Malin Premaratne; Saman K. Halgamuge (AAAI, 2024)

GINN-KAN: Interpretability pipelining with applications in Physics Informed Neural Networks. - Nisal Ranasinghe; Yu Xia; Sachith Seneviratne; Saman K. Halgamuge (CoRR, 2024)

Graph-Eq: Discovering Mathematical Equations using Graph Generative Models. - Nisal Ranasinghe; Damith A. Senanayake; Saman K. Halgamuge (CoRR, 2025)

FRAME-C: A knowledge-augmented deep learning pipeline for classifying multi-electrode array electrophysiological signals. - Nisal Ranasinghe; Dzung Do-Ha; Simon Maksour; Tamasha Malepathirana; Sachith Seneviratne; Lezanne Ooi; Saman K. Halgamuge (CoRR, 2025)