Multidisciplinary AI Research Centre University of Peradeniya
Contact us

Biography

Athulya Ratnayake is a Research Assistant at the Multidisciplinary AI Research Centre (MARC), University of Peradeniya. With a background in Electrical and Electronic Engineering, his work focuses on the intersection of artificial intelligence, applied mathematics, and data driven modelling. His research interests include computer vision, remote sensing, image denoising, hyperspectral imaging, semantic change detection, demographic analysis, and the mathematical foundations of machine learning.

At MARC, he is involved in interdisciplinary research projects in imaging, vision, and policy oriented data analysis. His current work includes semantic change detection, image denoising, hyperspectral image analysis, and a Demographic Analysis project that uses demographic structures together with modern learning algorithms to support data driven policy making.

Associated projects 1

Publications 7

  1. From Parallelism to Specialisation: SSA-Guided Multi-Branch Implicit Neural Representations

    Athulya Ratnayake, Buwaneka Epakanda, Sajana, Bogahawatta, Roshan Godaliyadda, Parakrama Ekanayake

    The Fifteenth International Conference on Learning Representations (ICLR 2027) · 2027

    Conference Under review Implicit Neural Representation

  2. Mamba-FCS: Joint Spatio-Frequency Feature Fusion, Change-Guided Attention, and SeK Inspired Loss for Enhanced Semantic Change Detection in Remote Sensing (opens in a new tab)

    Buddhi Wijenayake, Athulya Ratnayake, Praveen Sumanasekara, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Nichula Wasalathilaka

    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2026

    Journal Accepted Hyperspectral Unmixing DOI 10.1109/JSTARS.2026.3663066

  3. Preprocessing Algorithm Leveraging Geometric Modeling for Scale Correction in Hyperspectral Images for Improved Unmixing Performance (opens in a new tab)

    Praveen Sumanasekara, Athulya Ratnayake, Buddhi Wijenayake, Keshawa Ratnayake, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath

    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2026

    Journal Accepted Hyperspectral Unmixing DOI 10.1109/JSTARS.2026.3687834

  4. Devising PoPStat: A Metric Bridging Population Pyramids with Global Disease Mortality (opens in a new tab)

    Tharaka Fonseka, Buddhi Wijenayake, Athulya Ratnayake, Inosha Alwis, Supun Manathunga, Roshan Godaliyadda, Samath Dharmarathne, Vijitha Herath, Parakrama Ekanayake, Isuru Pamuditha

    2025

    Journal Demographic Analysis DOI 10.48550/arXiv.2501.11514

  5. PoPStat-COVID19: Leveraging Population Pyramids to Quantify Demographic Vulnerability to COVID-19 (opens in a new tab)

    Buddhi Wijenayake, Athulya Ratnayake, Lelumi Edirisinghe, Uditha Wijeratne, Tharaka Fonseka, Roshan Godaliyadda, Samath Dharmaratne, Parakrama Ekanayake, Vijitha Herath, Insoha Alwis, Supun Manathunga

    International Conference on Advances in ICT for Emerging Regions 2025 · 2025

    Conference Accepted Demographic Analysis DOI 10.48550/arXiv.2509.14213

  6. Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection (opens in a new tab)

    Buddhi Wijenayake, Athulya Ratnayake, Praveen Sumanasekara, Nichula Wasalathilaka, Mathivathanan Piratheepan, Roshan Godaliyadda, Mervyn Ekanayake, Vijitha Herath

    International Conference on Industrial and Information Systems 2025 · 2025

    Conference Accepted Hyperspectral Unmixing DOI 10.48550/arXiv.2507.11523

  7. Unsupervised learning reveals global demographic configurations and national trajectories from population pyramids

    Athulya Ratnayake, Lelumi Edirisnghe, Thisumi Wijesinghe, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Samath Dharmaratne

    Nature Humanities and Social Sciences Communications

    Journal Under review Demographic Analysis