Improved Learning from Small Data Sets Through Effective Combination of Machine Learning Tools with VSG Techniques. - Chathura Wanigasekara; Akshya Swain; Sing Kiong Nguang; B. Gangadhara Prusty (IJCNN, 2018)

Neural Network Based Inverse System Identification from Small Data Sets. - Chathura Wanigasekara; Akshya Swain; Sing Kiong Nguang; B. Gangadhara Prusty (IJCNN, 2019)

Delta-Modulator-Based Quantised Output Feedback Controller for Linear Networked Control Systems. - Chathura Wanigasekara; Dhafer Al-Makhles; Akshya Swain; Sing Kiong Nguang (IEEE Access, 2020)

Machine Learning Based Predictive Model for AFP-Based Unidirectional Composite Laminates. - Chathura Wanigasekara; Ebrahim Oromiehie; Akshya Swain; B. Gangadhara Prusty; Sing Kiong Nguang (IEEE Trans. Ind. Informatics, 2020)

Generalised Controller Design Using Continual Learning. - Diana Benavides Prado; Chathura Wanigasekara; Akshya Swain (ICANN (2), 2021)

Delta-Modulator-Based Quantised State Feedback Controller for T-S Fuzzy Networked Systems. - Chathura Wanigasekara; Liruo Zhang; Akshya Swain; Sing Kiong Nguang (Int. J. Fuzzy Syst., 2021)

Machine learning-based inverse predictive model for AFP based thermoplastic composites. - Chathura Wanigasekara; Ebrahim Oromiehie; Akshya Swain; B. Gangadhara Prusty; Sing Kiong Nguang (J. Ind. Inf. Integr., 2021)

H∞ State-Feedback Consensus of Linear Multi-Agent Systems. - Chathura Wanigasekara; Liruo Zhang; Akshya Swain (ICCA, 2022)

A comparative investigation between memory-based and discrete event-triggered scheme in networked control systems. - Liruo Zhang; Chathura Wanigasekara; Akshya Swain (ICCA, 2022)

Delta Modulator Based Quantised State-Feedback Control of Networked Linear Systems. - Dhafer J. Almakhles; Chathura Wanigasekara; Akshya Swain (IEEE Access, 2022)

Enhanced Fault Classification and Localization in Microgrids Using Machine Learning. - J. A. R. R. Jayasinghe; J. H. E. Malindi; R. M. A. M. Rajapaksha; V. Logeeshan; Chathura Wanigasekara (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; Sisil Kumarawadu; Chathura Wanigasekara (AIIoT, 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; Sisil Kumarawadu; V. Logeeshan; Chathura Wanigasekara (AIIoT, 2023)

Optimal Scheduling of a Solar-Powered Microgrid Using ML-Based Solar and Load Forecasting. - W. M. N. Witharama; K. M. D. P. Bandara; M. I. Azeez; Muditha Adhikari; Kasun Bandara; V. Logeeshan; Chathura Wanigasekara (AIIoT, 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; Sisil Kumarawadu; Chathura Wanigasekara (IEEE Access, 2023)

Robust Control of Autonomous Underwater Vehicles Using Delta-Sigma-Based 1-bit Controllers. - Chathura Wanigasekara; Frank Sill Torres; Akshya Swain (IEEE Access, 2023)

Self-Adaptive Non-Intrusive Load Monitoring Using Deep Learning. - S. M. L. Arampola; M. S. K. Nisakya; W. A. Yasodya; Sisil Kumarawadu; V. Logeeshan; Chathura Wanigasekara (AIIoT, 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; Sisil Kumarawadu; Chathura Wanigasekara (AIIoT, 2024)

Development of Deep Learning Model to Detect Cyber-Attacks within Vehicular Networks. - R. D. Sandakelum; V. H. Liyanage; P. M. Chandrasekara; V. Logeeshan; Sisil Kumarawadu; Chathura Wanigasekara (AIIoT, 2024)

Accurate Prediction of Remaining Useful Life for Lithium-ion Battery Cells Using Deep Neural Networks. - Shamaltha M. Wickramaarachchi; S. A. Dewmini Suraweera; D. M. Pasindu Akalanka; V. Logeeshan; Chathura Wanigasekara (AIIoT, 2024)

Consensus-Based Load Frequency Control of a Multi-Area Power System. - Ravi Patel 003; Chathura Wanigasekara; Akshya Swain; Abhisek Ukil (IEEE Access, 2024)

Advanced Genetic Algorithm for Optimal Microgrid Scheduling Considering Solar and Load Forecasting, Battery Degradation, and Demand Response Dynamics. - W. M. N. Witharama; K. M. D. P. Bandara; M. I. Azeez; Kasun Bandara; V. Logeeshan; Chathura Wanigasekara (IEEE Access, 2024)

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; Sisil Kumarawadu; Chathura Wanigasekara (IEEE Access, 2025)

Self-Adaptive Deep Learning Framework for Non-Intrusive Load Monitoring: Addressing Aging Appliance Challenges With Transfer Learning and Pseudo Labeling. - W. A. Yasodya; S. M. L. Arampola; M. S. K. Nisakya; V. Logeeshan; Sisil Kumarawadu; Chathura Wanigasekara (IEEE Access, 2025)

Optimal Control of Maritime Container Terminal Operations for Effective Utilization of Resources. - Bennet Greve; Naglaa M. Ahmed; Matthias Knauer; Chathura Wanigasekara; Frank Sill Torres (IEEE Trans. Intell. Transp. Syst., 2025)