S. Kumarawadu

According to our database, S. Kumarawadu authored at least 9 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of six.
• Erdős number of five.

2025

Mitigating Cyber Risks in Smart Cyber-Physical Power Systems Through Deep Learning and Hybrid Security Models.

M. A. S. P. Dayarathne, M. S. M. Jayathilaka, R. M. V. A. Bandara, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

IEEE Access, 2025

2024

Development of Deep Learning Model to Detect Cyber-Attacks within Vehicular Networks.

R. D. Sandakelum, V. H. Liyanage, P. M. Chandrasekara, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

Proceedings of the IEEE World AI IoT Congress, 2024

Deep Learning-Based Cyber Attack Detection in Power Grids with Increasing Renewable Energy Penetration.

M. A. S. P. Dayarathne, M. S. M. Jayathilaka, R. M. V. A. Bandara, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

Proceedings of the IEEE World AI IoT Congress, 2024

Self-Adaptive Non-Intrusive Load Monitoring Using Deep Learning.

S. M. L. Arampola, M. S. K. Nisakya, W. A. Yasodya, S. Kumarawadu, V. Logeeshan, Chathura Wanigasekara

Proceedings of the IEEE World AI IoT Congress, 2024

2023

Deep Learning Based Non-Intrusive Load Monitoring for a Three-Phase System.

Balarupan Gowrienanthan, N. Kiruthihan, K. D. I. S. Rathnayake, S. Kiruthikan, Logeeshan Velmanickam, S. Kumarawadu, Chathura Wanigasekara

IEEE Access, 2023

Neural Network-Based Pipeline for Detection of Sensor Anomalies in Battery Energy Storage Systems.

H. G. I. Thiranga, M. S. Weeraman, P. A. L. Pathirage, V. Logeeshan, S. Kumarawadu

Proceedings of the 17th IEEE International Conference on Industrial and Information Systems, 2023

A Data-Driven Approach Based on Artificial Neural Networks for the Detection and Classification of Bearing Anomalies in Power Generation Plants.

S. I. Senarathna, L. A. U. Prasanshi, S. D. W. Senanayake, Dhammike Wimalarathne, S. Kumarawadu, V. Logeeshan, Chathura Wanigasekara

Proceedings of the 2023 IEEE World AI IoT Congress (AIIoT), 2023

Maximizing Efficiency in Commercial Power Systems with an Optimized Load Classification and Identification Method Using Deep Learning and Ensemble Techniques.

M. J. S. Kulathilaka, S. Saravanan, H. D. H. P. Kumarasiri, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

Proceedings of the 2023 IEEE World AI IoT Congress (AIIoT), 2023

2022

Low-Cost Ensembling for Deep Neural Network based Non-Intrusive Load Monitoring.

Balarupan Gowrienanthan, N. Kiruthihan, K. D. I. S. Rathnayake, S. Kumarawadu, V. Logeeshan

Proceedings of the 2022 IEEE World AI IoT Congress (AIIoT), 2022