supunG

Mr. Supun Gajendrasinghe

Temporary Lecturer

Contact

Profile

Supun Chandana Gajendrasinghe is a Temporary Lecturer at NSBM Green University, Sri Lanka, with an academic background in Engineering Technology, specializing in Instrumentation and Automation, and Computer Science. His academic and professional interests span embedded systems, computer architecture, Internet of Things (IoT), and energy-efficient computing. His research focuses on developing energy-efficient architectures for edge computing, deep-learning-based computer vision, and intelligent embedded systems. He has experience in teaching undergraduate computing and engineering modules, coordinating academic activities, and contributing to research and technology-related initiatives. His current research interests emphasize sustainable and intelligent computing solutions through hardware–software co-design, FPGA-based architectures, AIoT, and edge intelligence.

Research Interests

  • Energy-Efficient Computing Architectures
  • Edge Computing and Edge Intelligence
  • Artificial Intelligence of Things (AIoT)
  • Internet of Things (IoT) and Embedded Systems
  • FPGA-Based System Design and Hardware–Software Co-Design
  • Computer Architecture and RISC-V-Based Systems

Memberships

  • IEEE – Professional ( Member ID – 100447574 )

Journal Publications

  1.  Basnayake, R.N.I. and Gajendrasinghe, G.M.S.C., 2026. Human-In-The-Loop AI for Precision Agriculture: Scoping Review. International Journal of Latest Technology in Engineering, Management & Applied Science, 15(2), pp.712–719. Available at: https://doi.org/10.51583/IJLTEMAS.2026.15020000061
  2. Gajendrasinghe, G.M.S.C. and Perera, M.D.R., 2026. Concept Paper on Design and Optimization of Energy-efficient Architectures for Edge Computing. International Journal of Latest Technology in Engineering, Management & Applied Science, 15(2). Available at: https://doi.org/10.51583/IJLTEMAS.2026.15020000068
  3. Basnayake, R.N.I., Gajendrasinghe, G.M.S.C. and Dissanayake, C., 2026. Integrating Artificial Intelligence with Plant Electrophysiology for Early Stress Diagnosis: A Scoping Review. International Journal of Research and Scientific Innovation (IJRSI), 12(13), pp.194–201. Available at: https://doi.org/10.51244/IJRSI.2025.1213CS001

Conference Publications

  1. Gajendrasinghe, G.M.S.C., Abeysiri, K.M.S.D., Rathnayake, I.M. and Atapattu, H.Y.R. (2023) ‘Deep learning driven mobile robot to detect and classify tomato leaf diseases’, Proceedings of the International Conference on Applied and Pure Sciences (ICAPS 2023), Faculty of Science, University of Kelaniya, Sri Lanka, abstract MO-18, p. 140. Available at: https://conf.kln.ac.lk/icaps/media/attachments/2023/12/11/icaps-2023-proceedings—final—27-10-20231.pdf.
  2. Gunarathna, H., Jayamanne, J., Silva, E., Roshan, K., Shafraz, M. and Gajendrasinghe, G.M.S.C. (2025) ‘NOTESNAP – AI powered Chrome extension for web-based note-taking and summarization’, NSBM Student Research Symposium on Innovative Technology, p. 38.

On-Going Research

  • Design and Optimization of Energy-Efficient Architectures for Edge Computing
  • Energy-Efficient AIoT and Edge Intelligence

Research and Project Contributions to the Sustainable Development Goals (SDGs)

His research and other project contributions are aligned with the following SDG(s):