Publications

S. Weerasinghe and T. Cerny, ‘A Neuro-Symbolic Risk Calculus for Quantifying Security Posture in Microservice Systems', in International Conference on Evaluation and Assessment in Software Engineering (EASE) 2026, Galsgow, Scotland, Jun. 2026.

S. Weerasinghe, Amr Abdelfattah, and T. Cerny, ‘GADM-Oracle: A Domain-Adaptive Oracle for Detecting "Data Bugs" in Enterprise Data Stacks’, in 2026 34th ACM International Conference on the Foundations of Software Engineering, Montreal, Canada: ACM, July. 2026, pp.1-11.

S. Weerasinghe, B.D. Mach, A. Zaslavsky, and V. Moghaddam, ‘Unlocking Contextual Intelligence - Anywhere, Anytime, and Everywhere’, in 2025 26th IEEE International Conference on Mobile Data Management (MDM), Irvine, California, USA: IEEE, Jun. 2025, , pp. 1-7, doi: 10.1109/MDM65600.2025.00050.

S. Weerasinghe, K. S. Jagarlamudi, A. Zaslavsky, S. W. Loke, K. Lee and G. -L. Huang, "Improving the Usefulness of Context Information for IoT Applications: A Middleware-based Approach," 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Biarritz, France, 2024, pp. 1-7, doi: 10.1109/PerComWorkshops59983.2024.10503179.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, and G. Li-Huang, ‘Proactive Context Caching Based on Situation Prediction for Real-Time Mobile IoT Applications’, in 2024 25th IEEE International Conference on Mobile Data Management (MDM), Brussels,  Belgium: IEEE, Jun. 2024, pp. 313-3158, doi: 10.1109/MDM61037.2024.00064.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Abken, A. Hassani, and A. Medvedev, ‘Adaptive Context Caching for Efficient Distributed Context Management Systems’, in ACM Symposium on Applied Computing, Tallinn, Estonia: ACM, Mar. 2023, p. 10. doi: 10.1145/3555776.3577602.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, V. Moghaddam, and C. Becker, ‘Towards World Wide Context Management: Architecting Distributed Contextual Intelligence Systems for Real-Time IoT Applications’, in 2023 24th IEEE International Conference on Mobile Data Management (MDM), Singapore, Singapore: IEEE, Jul. 2023, pp. 340–345. doi: 10.1109/MDM58254.2023.00062.

Ashish Manchanda, Prem Prakash Jayaraman, Abhik Banerjee, Arkady Zaslavsky, Shakthi Weerasinghe, and Guang-Li Huang, ‘A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications’, in EAI MobiQuitous, Melbourne, Australia: Springer, November 2023, p. 16. doi: 10.1007/978-3-031-63989-0_8.

C. Bombuwala, K. Kahatapitiya, R. Kumaranayaka, S. Weerasinghe, U. Ganegoda, and I. Manawadu, ‘Event Driven Share Price Forecasting based on Change based Impact Analysis’, in 2022 7th International Conference on Information Technology Research (ICITR), Moratuwa, Sri Lanka: IEEE, Dec. 2022, pp. 1–6. doi: 10.1109/ICITR57877.2022.9992415.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Medvedev, and A. Abken, ‘Estimating the Lifetime of Transient Context for Adaptive Caching in IoT Applications’, in ACM Symposium on Applied Computing, Brno, Czech Republic: ACM, Apr. 2022, p. 10. doi: 10.1145/3477314.3507075.

S. Weerasinghe and S. Ahangama, ‘Predictive Maintenance and Performance Optimisation in Aircrafts using Data Analytics’, in 2018 3rd International Conference on Information Technology Research (ICITR), Moratuwa, Sri Lanka: IEEE, Dec. 2018, pp. 1–8. doi: 10.1109/ICITR.2018.8736157

Md Arfan Uddin, S. Weerasinghe, Darek Gajewski, Melika Akbarsharifi, Roxana Akbarsharifi, Christopher Stoner, Tomas Cerny and Sen He, ‘Microservice Logs Analysis Employing AI: A Systematic Literature Review’, Journal of Systems and Software. https://doi.org/10.1016/j.jss.2026.112786

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Abken, A. Hassani, and G.-L. Huang, ‘Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems’, ACM Trans. IoT, p. 30, Feb. 2024, doi: 10.1145/3648571.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Hassani, A. Medvedev, and A. Abken, ‘Adaptive Context Caching for IoT-Based Applications: A Reinforcement Learning Approach’, Sensors, vol. 23, no. 10, p. 4767, May 2023, doi: 10.3390/s23104767.

A. Medvedev, A. Hassani, G. Belov, S. Weerasinghe, G. Huang, A. Zaslavsky, S. W. Loke, and P. Jayaraman, ‘Refresh Rate Based Caching and Prefetching Strategies for Intenet of Things Middleware’, Sensors, vol. 23, no. 21, p. 8779, October 2023, doi: 10.3390/s23218779.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Medvedev, and A. Abken, ‘Estimating the dynamic lifetime of transient context in near real-time for cost-efficient adaptive caching’, SIGAPP Appl. Comput. Rev., vol. 22, no. 2, pp. 44–58, Jun. 2022, doi: 10.1145/3558053.3558057.

S. Weerasinghe, A. Udadeniya, N. Waduge, R. de Zoysa, and U. Ganegoda, ‘Novel Method to Analyze and Forecast Social Impact on Macro- and Micro-Economies Using Social Media Data’, in Proceedings of International Conference on Sustainable Expert Systems, S. Shakya, V. E. Balas, W. Haoxiang, and Z. Baig, Eds., in Lecture Notes in Networks and Systems, vol. 176. Singapore: Springer Singapore, 2021, pp. 261–277. doi: 10.1007/978-981-33-4355-9_21.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Medvedev, A. Abken, and A. Hassani, ‘Context Caching for IoT-Based Applications: Opportunities and Challenges’, IEEE Internet Things M., vol. 6, no. 4, pp. 96–102, Dec. 2023, doi: 10.1109/IOTM.001.2200247.

Shakthi Weerasinghe, "A No-Code Composable Pipeline for Holistic Microservice Assurance", in 2026 23rd IEEE International Conference on Software Architecture (ICSA) 2026, Amsterdam, Netherlands, IEEE, June, 2026, pp.1-4.

S. Weerasinghe, and T. Cerny, ‘A Holistic Risk Calculus for Microservice Systems using Multi-Source Signal Fusion’, in 2026 34th ACM International Conference on the Foundations of Software Engineering, Montreal, Canada: ACM, July. 2026, pp.1-5.

Weerasinghe, Shakthi and Malik, Mohsin and Andargoli, Amir and Morrow, Guy and Jayaraman, Prem Prakash and Forkan, Abdur, Are Algorithmic Biases in AI-Based Recommendations Real? An Activity Theory Framing of Digital Music Streaming (November 22, 2025). Available at SSRN: https://ssrn.com/abstract=5784803 or http://dx.doi.org/10.2139/ssrn.5784803

Uddin, Md Arfan and Weerasinghe, Shakthi and Gajewski, Darek and Akbarsharifi, Melika and Akbarsharifi, Roxana and Stoner, Christopher and Cerny, Tomas and He, Sen, Microservice Logs Analysis Employing AI: A Systematic Literature Review. Available at SSRN: https://ssrn.com/abstract=5768479 or http://dx.doi.org/10.2139/ssrn.5768479

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Abken, and A. Hassani, ‘Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems’. arXiv, Dec. 22, 2022. Accessed: Dec. 23, 2022. [Online]. Available: http://arxiv.org/abs/2212.11709

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Hassani, A. Abken, and A. Medvedev, ‘From Traditional Adaptive Data Caching to Adaptive Context Caching: A Survey’, arXiv:2211.11259 [cs.HC], p. 35, Nov. 2022.

S. Weerasinghe, U. Ganegoda, C. Bombuwela, K. Kahatapitiya, and R. Kumaranayaka, ‘Architecting an event-driven forecasting model for stock market variations’, p. 9.

Shakthi Weerasinghe, Mohsin Malik, Guy Morrow, Amir Andargoli, Prem Prakash Jayaraman, and Abdur Forkan, ‘Examining Digital Platform Interactions to Assess the Performance of Australian Artists on Algorithmic Playlists’. Victorian Music Development Office (VMDO), Feb. 06, 2026. [Online]. Available: https://www.vmdo.com.au/dsp-algorithm-research 

Shakthi Weerasinghe, ‘Technical Document on Carbon Footprint Estimation Project for Sphere’. Swinburne University of Technology, Nov. 2024. (Handed over to Sphere For Good).