Rate My Professor Nimsiri Abhayasinghe

Dr. Nimsiri Abhayasinghe is a Senior Lecturer in the School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) within the Faculty of Science and Engineering at Curtin University. He earned his B.Sc. Engineering (Honours) in Electronic and Telecommunication Engineering from the University of Moratuwa, Sri Lanka, and completed his PhD at Curtin University. With nearly 20 years of experience in academia, Dr. Abhayasinghe specializes in teaching Electronic and Embedded Systems. His career includes appointments at Curtin University as Senior Lecturer since July 2023 and as Head of the Department of Electrical and Electronic Engineering at the Sri Lanka Institute of Information Technology (SLIIT), where he has served in senior lecturing roles since earlier in his career.

Dr. Abhayasinghe's research interests focus on gait analysis, inertial sensors, pedestrian navigation, and indoor positioning. These areas have practical applications in assistive technologies, such as indoor localization systems for visually impaired individuals using thigh-mounted inertial measurement units (IMUs) and mobile devices. He has published over 15 peer-reviewed papers, including 'Human Gait Phase Recognition Based on Thigh Movement Computed Using IMUs' (2014, co-authored with Iain Murray), 'A Gyroscopic Data Based Pedometer Algorithm' (2016), 'Human Gait Modeling, Prediction and Classification for Level Walking Using Harmonic Model' (2022), 'Efficient, Authentication and Access Control Implementation in Mobile Ad hoc Networks' (2012, co-authored with Prabath Lakmal Rupasinghe and Iain Murray), and 'A Context-Aware Doorway Alignment System with Depth Estimation for Intelligent Wheelchairs' (2025, co-authored with Shanelle Tennekoon, Nushara Wedasingha, Anuradhi Welhenge, and Iain Murray). His Google Scholar profile records 345 citations. At Curtin University, he contributes to supervisory roles in projects like engineering smarter wheelchairs for safer independence. Additionally, his work explores human activity recognition, step counting, and stride length estimation using gyroscopic data from thigh movements during walking, sitting, and standing.