Udayanga received his Bsc.Eng degree in Computer Science and Engineering and MSc degree in Electronics and Automation from the University of Moratuwa, Sri Lanka. Before joining the AERO-TRAIN project he worked as a software Engineer at Synopsys (pvt) Ltd and probationary lecturer at University of Ruhuna Sri Lanka. His research interests are on machine learning, computer vision and digital system design.
His PhD project aims to use bio-inspired machine learning approaches for anomaly detection and condition monitoring of some selected urban structures using aerial robots.
Some objectives of the project are,
Improve the state-of-art deep learning approaches to detect and classify both known and unknown structural anomalies
Implement bio-inspired learning approaches such as Spiking neural networks(SNNs) to improve the online anomaly detection and classification efficiency and training efficiency
Investigate the applicability of neuromorphic processors and event cameras together with SNNs for structural anomaly detection and classification.