Hirushi

Ms. Hirushi Dilpriya

Lecturer Probationary

Contact

  • hirushi.d@nsbm.ac.lk
  • +94 11 544 5000 ( Ext: 1238)
  • Department of Computer and Data Science
  • Faculty of Computing
  • Google Scholar
  • Linkedin

Profile

Ms. Hirushi Dilpriya Thilakarathna received a Bachelor of Science (Hons.) Degree in Mathematics with the first class from the University of Sri Jayewardenepura, Sri Lanka. She was the gold medalist from the Department of Mathematics in 2020: A Department Award Dr. Sunethra Weerakoon Memorial Gold Medal; and Dr. Srimathi Wewala Gold Medal for the best performance in Mathematics. Upon completing her first degree, currently, she is reading for her Master of Philosophy (MPhil) at the University of Sri Jayewardenepura. It is related to subject areas in Business Statistics, Actuarial Science, and Data Science. She started her career as a teaching instructor andbecame a temporary lecturer at her University. Currently, she works in the school of computing of NSBM and delivers lectures in Advanced Mathematics, Probability, Inference, Descriptive Statistics, and computational thinking development.

Research Interests

  • Actuarial Science
  • Financial Mathematics
  • Mathematical Modelling
  • Computational Mathematics
  • Numerical MethodsDiscrete Mathematics
  • Regression Analysis
  • Functional Analysis
  • Telecommunication Network

Memberships

  • IEEE 
  • CSSL Associate membership

Journal Publications

Journal Publications

  1. Senarathna, W.D.J.I. and Dilpriya, T.A.H., 2026. Deep learning based district level paddy production forecasting: a study based on agricultural behaviour in Sri Lanka. In: 2026 6th International Conference on Advanced Research in Computing (ICARC). Belihuloya, Sri Lanka, 2026. IEEE, pp.1–6. doi:10.1109/ICARC68737.2026.11453891.
  2. Senarathna, W.D.J.I. and Dilpriya, T.A.H., 2026. Dr. BlueWhale: an AI-powered automated deep research assistant with multi-LLM integration for academic and professional investigation. In: 2026 IEEE International Research Conference on Smart Computing and Systems Engineering (SCSE). Kelaniya, Gampaha, Sri Lanka, 2026. IEEE, pp.1–6. doi:10.1109/SCSE70081.2026.11499793.
  3. Liyanage, N. and Dilpriya, T.A.H., 2026. Anomaly detection approach for remote beehive health assessment via environmental patterns. In: 2026 IEEE International Research Conference on Smart Computing and Systems Engineering (SCSE). Kelaniya, Gampaha, Sri Lanka, 2026. IEEE, pp.1–6. doi:10.1109/SCSE70081.2026.11499959.
  4. Senarathna, W.D.J.I. and Dilpriya, T.A.H., 2026. A systematic comparative evaluation of machine learning and deep learning models for EEG-based epileptic seizure prediction with clinical deployment guidelines. In: 2026 IEEE International Research Conference on Smart Computing and Systems Engineering (SCSE). Kelaniya, Gampaha, Sri Lanka, 2026. IEEE, pp.1–6. doi:10.1109/SCSE70081.2026.11499844.
  5. Senarathna, W.D.J.I. and Dilpriya, T.A.H., 2026. Intelligent EcoETL: an energy-aware framework for sustainable extract-transform-load operations in big data processing. In: D. Tantrigoda et al., eds. Selected Articles from the International Conference on Emerging Concepts and Research in Integrated Sustainable Adaptation, ECRISA 2026. Proceedings in Technology Transfer. Singapore: Springer. doi:10.1007/978-981-92-0423-6_11.
  6. Senarathna, W.D.J.I. and Dilpriya, T.A.H., 2026. Sustainable urban redesign framework integrating energy efficiency, active mobility, and green infrastructure for tropical developing cities: empirical study for Colombo 05. In: 2026 6th International Conference on Electrical, Computer and Energy Technologies (ICECET). Rome, Italy, 2026. IEEE, pp.1–6. doi:10.1109/ICECET65726.2026.11632310.
  7. Dilpriya, T. A. H., Lanel, G. H. J., and Perera, M. T. M., (2023) ‘Reviewing the efficacy of Federal Reserve Bank Reserve policies through a time series analysis of the effective federal funds rate’, International Journal of Research and Innovation in Social Science, VII(IV), pp. 869–880. doi:10.47772/ijriss.2023.7472.
  8. Dilpriya, T. A. H, Lanel, G. H. J., and Vidanage, B. V. N. C., (2022) ‘A strategy to strengthen and enhance the telecommunication network in Sri Lanka by using concepts of graph theory and linear programming models’, International Journal of Natural Sciences Research, 10(1), pp. 1–20. doi:10.18488/63.v10i1.2913.
 

Books/Book Chapters

  1. Dilpriya, TAH , Sanjeewa, R. (2018) Prediction of Heart Diseases Using Neural Network and construct a Minimum Spanning Tree from Risk Factors by Correlation, 74-96.

Ongoing Research

  1. Mathematical models for financial bubbles and crashes (work-in-process)

Research and Project Contributions to the Sustainable Development Goals (SDGs)

Her research and other project contributions are aligned with the following SDG(s):