Staff Profile

• Chairman, Research Committee, Faculty of Applied Science, 2019 to date
• Chairman, Handbook Committee, Faculty of Applied Science, 2019 to date
• Coordinator, Auxiliary Course Units, Faculty of Applied Science, 2018 -2020
• Activity Coordinator, AHEAD Project, Faculty of Applied Science. 2019 to date
• Member, Curriculum Evaluation Committee, University of Jaffna, 2020 to date
• Academic Advisor- Faculty of Applied Science, 2018 to date.
• Member-Program Review – 2019 to date.
• Member of the Senate of the University of Jaffna, June 2019 to date
• Senior Treasurer, Faculty of Applied Science Student’s Union. 2018 to 2020
• Senior Treasurer, ICTCS, Department of Physical Science, 2019 to 2020
• Member of IT Committee, Vavuniya Campus, 2016-to date
• Member of the Faculty level Curriculum Evaluation Committee, Faculty of Applied Science, 2017 to date
• Member, Vavuniya Campus Research Symposium -2017
• Editor, Proceedings of Vavuniya Campus Research Symposium -2017
• Member – Vavuniya Campus Newsletter 2016-2017
• Chairman- Vanni Career Fair – 2016, Vavuniya Campus, 2016
• Coordinator – Career Guidance Unit, Vavuniya Campus, 2016-2017
• Chairman, Technical Evaluation Committee for “MS Project 2016” Software, Vavuniya Campus, 2017
• Inquiry Officer – Vavuniya Campus, 2017.

Undergraduate Teaching

• Introduction to Programming
• Database Systems
• Computer Security
• Software Engineering
• Computer Graphics
• Graph Theory
• Research Methodology and Scientific Writing
• Advance Database System
• Parallel Computing
• Digital Image Processing
• Cryptography

Research Interests

1. Medical Image Computing

2. Neuroimaging, MRI, Diffusion MR Imaging

3. Human Connectome

4. Specialties: Diffusion MR Imaging and Fiber Tractography

Reviewer

MICCAI-2019 MICCAI-2020

Journals

1. Subaramya Srivishagan, Logiraj Kumaralingam, Kokul Thanikasalam, U.A.J. Pinidiyaarachchi, Nagulan Ratnarajah, Discriminative Patterns of White Matter Changes in Alzheimer’s, Psychiatry Research: Neuroimaging, 2022, 111576, ISSN 0925-4927, https://doi.org/10.1016/j.pscychresns.2022.111576.

2. Surendran, S.N.; Nagulan, R.; Tharsan, A.; Sivabalakrishnan, K.; Ramasamy, R. Dengue Incidence and Aedes Vector Collections in Relation to COVID-19 Population Mobility Restrictions. Trop. Med. Infect. Dis. 2022, 7, 287. https://doi.org/10.3390/tropicalmed7100287 

3. Surendran, S.N., Nagulan, R., Sivabalakrishnan, K. et al. Reduced dengue incidence during the COVID-19 movement restrictions in Sri Lanka from March 2020 to April 2021. BMC Public Health 22, 388 (2022). https://doi.org/10.1186/s12889-022-12726-8 

4. Srivishagan S, Perera AAI, Hojjat A, Ratnarajah N. Brain Network Measures for Groups of Nodes: Application to Normal Aging and Alzheimer’s Disease. Brain Connect. 2020;10(6):316-327. doi:10.1089/brain.2020.0747 

5. Poh JS, Li Y, Ratnarajah N, Fortier MV, Chong YS, Kwek K, Saw SM, Gluckman PD, Meaney MJ, Qiu A. Developmental synchrony of thalamocortical circuits in the neonatal brain. Neuroimage. 2015 Aug 1; 116:168-176.

6. Lee A, Ratnarajah N, Tuan TA, Chen SH, Qiu A. Adaptation of brain functional and structural networks in aging. PLoS One. 2015 Apr 15; 10(4):e0123462.

7. Ratnarajah N, Qiu A. Multi-Label Segmentation White Matter Structures: Application to Neonatal Brains. Neuroimage, 2014 Nov 15. 102, Part 2, 913–922.

8. Jin Thong JY, Du J, Ratnarajah N, Dong Y, Soon HW, Saini M, Tan MZ, Tuan Ta A, Chen C, Qiu A. Abnormalities of cortical thickness, subcortical shapes, and white matter integrity in subcortical vascular cognitive impairment. Hum Brain Mapping. 2014 May. 35 (5), 2320-2332.

9. Ratnarajah N, Rifkin-Graboi A, Fortier MV, Chong YS, Kwek K, Saw SM, Godfrey KM, Gluckman PD, Meaney MJ, Qiu A. Structural connectivity asymmetry in the neonatal brain. Neuroimage .2013 Jul. 75, 187-194.

10. Ratnarajah N, Simmons A, Bertoni M, Hojjatoleslami A. Two-Tensor Model-Based Bootstrapping on Classified Tensor Morphologies: Estimation of Uncertainty in Fibre Orientation and Probabilistic Tractography, Magnetic Resonance Imaging. 2013 Feb. 31(2), 296-312.

11. Ratnarajah, N, Simmons A, Davydov O, and Hojjatoleslami A, A Novel Approach for Improved Tractography and Quantitative Analysis of Probabilistic Fibre Tracking Curves. Medical Image Analysis. 2012 Jan. 16(1), 227-238.

12. Bertoni MA, Sakel M, Hojjattoleslami A, Bertoni IV, Ratnarajah N. Neuroimaging assessment of spasticity developed after acquired brain injuries and multiple sclerosis. Neuroradiol J. 2012 Jul. 25(3), 311-317.

MICCAI

1. Kumaralingam, L., Thanikasalam, K., Sotheeswaran, S., Mahadevan, J., Ratnarajah, N. (2022). Segmentation of Whole-Brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022. MICCAI 2022. Lecture Notes in Computer Science, vol 13431. Springer, Cham. https://doi.org/10.1007/978-3-031-16431-6_18 

2. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. Probabilistic Clustering and Shape Modelling of White Matter Fibre Bundles using Regression Mixtures. MICCAI, 2011; 14 (Pt 2); LNCS 6892, 25-32.

3. Ratnarajah, N, Simmons, A, Davydov, O and Hojjatoleslami, A. A Novel White Matter Fibre Tracking Algorithm using Probabilistic Tractography and Average Curves. MICCAI, 2010, Part I, LNCS 6361, 666-673.

Conferences

1. W.M. Uresha Senani, S. Thirukumaran, Ranuki Reheshini Arandara, and Nagulan Ratnarajah  “A Machine Learning Approach for Early Detection of Thyroid Disorders in Sri Lankan Women”  IEEE 11th International Conference on Moratuwa Engineering Research Conference 2025 (MERCon 2025), Sri Lanka, August 2025.

2. Nirupa Ariyaraththinam, Bramya Sinthathurai, Keerthanaram Thanabalasingam, Jeyamugan Thirunavukkarasu, and Nagulan Ratnarajah  “Deep Learning-Based Coral Reef Segmentation: A Satellite Imagery Study of the Trincomalee District”  IEEE 11th International Conference on Moratuwa Engineering Research Conference 2025 (MERCon 2025), Sri Lanka, August 2025

3. P. Sivasothy, L. Kumaralingam, T. Jegatheeswaran, S. Srivishagan, K. Thanikasalam and N. Ratnarajah, “Functional Biomarkers of Alzheimer’s Disease: Explainable AI using Resting-State fMRI,” 2025 5th International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2025, pp. 1-6, doi: 10.1109/ICARC64760.2025.10962861. 

4. J. Sounthararajah, L. Kumaralingam, T. Jegatheeswaran, S. Srivishagan, K. Thanikasalam and N. Ratnarajah, “Classification of Alzheimer’s Disease Stages using Weighted Brain Connectivity based Graph Convolutional Neural Network,” 2025 5th International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2025, pp. 1-6, doi: 10.1109/ICARC64760.2025.10963110. 

5. W. R. G. A. D. P Herath, Logiraj Kumaralingam, S.Bramya, V.Vinoharan, Nagulan Ratnarajah “Adapting Prompt-Driven Approach for Diabetic Foot Ulcer Segmentation: A Sri Lankan Patient Study” IEEE 9th International Conference on Advances on Technology and Computing 2024 (ICATC 2024), Sri Lanka, August 2024.

6.  Sangeetha Mahendran, Jenusiya Jeyaseelan, and  Nagulan Ratnarajah “Efficient Parallelization of Global Graph Measures on Multicore Shared Memory Systems”  IEEE 10th International Conference on Moratuwa Engineering Research Conference 2024 (MERCon 2024), Sri Lanka, August 2024.

7. Mathumitha Vathanakumar and Nagulan Ratnarajah “A Review on White Matter Changes in Parkinson’s Disease Detected by Diffusion MRI”  IEEE 10th International Conference on Moratuwa Engineering Research Conference 2024 (MERCon 2024), Sri Lanka, August 2024.

8. T. Jegatheeswaran, L. Kumaralingam, S. Selvarajah and N. Ratnarajah, “Explainable Hybrid CNN Swin-Transformer Network for Tuberculosis Diagnosis in Chest X-Rays of Sri Lankan Patients,” 2024 4th International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2024, pp. 85-90.

9. Jenusiya J, Subaramya S, Nagulan R, “An Inverse Study of Centrality Measures for Node Groups: Application to Brain Networks“, IEEE 5th International Conference on Advancements in Computing 2023 (ICAC 2023), Sri Lanka, December 2023.  [ICAC 2023 -Overall Best research paper of the conference]

10. Tharaha N, Logiraj K, Keerthanaram T, Jeyamugan T, Nagulan R, “Automatic Identification of Sri Lankan Butterfly Families using Ensemble Deep Learning“, IEEE 5th International Conference on Advancements in Computing 2023 (ICAC 2023), Sri Lanka, December 2023.

11. Subaramya, S., Logiraj.K, Nagulan, R., Kokul, T., A., Pinidiyaarachchi, U.A.J., “Exploring Asymmetrical White Matter Abnormalities in Alzheimer’s Using Deep Learning” IEEE 9th International Conference on Moratuwa Engineering Research Conference 2023 (MERCon 2023), Sri Lanka, November 2023 [Accepted]

12. D.V. Dissanayake, S. Sobana, and B. Yogarajah, Nagulan Ratnarajah “Chronic Kidney Disease Detection using Machine Learning Algorithms: A Sri Lankan Study”, In IEEE International Conference on Advanced Research in Computing (ICARC’23), February 2023

13. S. Subaramya, T. Kokul, R. Nagulan, U.A.J. Pinidiyaarachchi, Graph Neural Network based Alzheimer’s Disease Classification using Structural Brain Network,  IEEE 22nd International Conference on Advances in ICT for Emerging Regions (ICTer), Sri Lanka. 2022.

14. Logiraj,K., Kokul,T., Sotheeswaran,S., Nagulan,R., “TractNet: A Deep Learning Approach on 3D Curves for Segmenting White Matter Fibre Bundles” IEEE 21st International Conference on Advances in ICT for Emerging Regions (ICTer), Sri Lanka. 2021.

15. Vigneswaran.P, Nagulan,R., “Detection of Wildlife Animals using Deep Learning Approaches: A Systematic Review” IEEE 21st International Conference on Advances in ICT for Emerging Regions (ICTer), Sri Lanka. 2021.

16. S. Subaramya, T. Kokul, R. Nagulan, U. A. J. Pinidiyaarachchi and M. Jeyasuthan, “Detection of Alzheimer’s Disease using Structural Brain Network and Convolutional Neural Network,” 2021 10th International Conference on Information and Automation for Sustainability (ICIAfS), 2021, pp. 173-178, doi: 10.1109/ICIAfS52090.2021.9606008.  

17. K. Logiraj, S. Sotheeswaran, M. Jeyasuthan and N. Ratnarajah, “Clustering of Major White Matter Bundles using Tract-specific Geometric Curve Features,” 2021 10th International Conference on Information and Automation for Sustainability (ICIAfS), 2021, pp. 506-511, doi: 10.1109/ICIAfS52090.2021.9606130.  

18. S. Selvaratnam, B. Yogarajah, T. Jeyamugan and N. Ratnarajah, “Feature selection in automobile price prediction: An integrated approach,” 2021 International Research Conference on Smart Computing and Systems Engineering (SCSE), 2021, pp. 106-112, doi: 10.1109/SCSE53661.2021.9568288. 

19.  G. Sittampalam and N. Ratnarajah, “Enhanced Symmetric Cryptography for IoT using Novel Random Secret Key Approach,” 2020 2nd International Conference on Advancements in Computing (ICAC), Malabe, Sri Lanka, 2020, pp. 398-403, doi: 10.1109/ICAC51239.2020.9357316. 

20. V. Palanisamy, V. Thiruchenthooran, S. N. Surendran and N. Ratnarajah, “Algorithms for Automatic Identification and Analysis of Sri Lankan Anopheles Mosquito Species,” 2020 2nd International Conference on Advancements in Computing (ICAC), Malabe, Sri Lanka, 2020, pp. 452-457, doi: 10.1109/ICAC51239.2020.9357228. 

21. G. T. Pathirana, S. Sotheeswaran and N. Ratnarajah, “Efficient Parallel GCD Algorithms for Multicore Shared Memory Architectures,” 2020, IEEE, 20th International Conference on Advances in ICT for Emerging Regions (ICTer), Colombo, Sri Lanka, 2020, pp. 272-273,  doi: 10.1109/ICTer51097.2020.9325430. 

22. G. Sittampalam and N. Ratnarajah, SAMS: An IoT Solution for Attendance Management in Universities, TENCON 2019 – 2019 IEEE Region 10 Conference (TENCON), Kochi, India, 2019, pp. 251-256.  doi: 10.1109/TENCON.2019.8929616

23.  PM Kumarage, B Yogarajah, N Ratnarajah, Efficient Feature Selection for Prediction of Diabetic Using LASSO, IEEE International Conference on Advances in ICT for Emerging Regions, Colombo, pp 1-7. 2019. DOI: 10.1109/ICTer48817.2019.9023720 

24. K Ganeshamoorthy, N Ratnarajah, On the Performance of Parallel Back-Propagation Neural Network Implementations Using CUDA, CATA 2017, Honolulu, Hawaii, USA.

25. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. Two-Tensor Model-Based Bootstrapping on Classified Tensor Morphologies: Estimation of Uncertainty in Fibre Orientation and Probabilistic Tractography. CDMRI, MICCAI, Toronto, Canada, 2011.

26. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. Probabilistic Clustering of White Matter Fibre Bundles using Regression Mixtures. Medical Image Understanding and Analysis Proceedings, London, 251-255, 2011.

27. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. Residual Bootstrapping on Classified Tensor Morphologies using Constrained Two-Tensor Model. Medical Image Understanding and Analysis Proceedings, London, 87-91, 2011.

28. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. Two-Tensor Residual Bootstrapping on Classified Tensor Morphologies. In Proc. ISMRM 19th Annual Meeting, p.4207, Montréal, Québec, Canada, May 2011.

29. Ratnarajah, N, Simmons, A, Colchester, A and Hojjatoleslami, A. Resolving complex fibre configurations using two-tensor random-walk stochastic algorithms. Proc. SPIE Medical Imaging, 79620R, Florida, USA. https://doi.org/10.1117/12.878065 

30. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. A Novel Average Curves Tractography Technique – Validation Using a Physical Phantom.  In Proc. Joint Annual Meeting ISMRM-ESMRMB, p. 4014, Stockholm, Sweden, 2010.

31. Ratnarajah, N, Simmons, A, Davydov, O and Hojjatoleslami, A. An error analysis of probabilistic fibre tracking methods: average curves optimization. In: Medical Image Understanding and Analysis, Kingston University, London, 134-138, 2009. 

32. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. Stochastic Fibre Tracking: An Average Curves Approach.  In Proc. ISMRM 17th Annual Meeting, p.1436, Honolulu, Hawaii, USA, 2009.

33. Ratnarajah, N, Simmons, A, and Hojjatoleslami, A. Stochastic Two-tensor Fibre Tractography. Medical Image Understanding and Analysis Proceedings, Dundee, UK. 194-198, 2008.