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Dr MD Moniruzzaman

Lecturer

Staff Member Details
Mobile: 0416 432 649
Email: m.moniruzzaman@ecu.edu.au
Campus: Joondalup  
Room: JO5.228  
ORCID iD: https://orcid.org/0000-0003-1130-7078

Dr MD Moniruzzaman is a Lecturer in ECU School of Engineering.

He completed his PhD in Artificial Intelligence, Deep Learning, and Robotics at Edith Cowan University in 2023. Prior to that, he obtained a Master of Science in Computer Science from ECU in 2019 and a Bachelor of Science in Electrical & Electronic Engineering from Khulna University of Engineering & Technology (KUET) in 2010.

His research interests lie in artificial intelligence, deep learning, and image and signal processing in the fields of robotics, electrical engineering, computer vision, and medical diagnostics. He has made contributions to robotics, teleoperation enhancement, and healthcare automation, AI-driven diagnostic tools for cardiovascular diseases with multiple high-impact journal publications.

Dr Moniruzzaman has published in leading journals and conferences, with his research receiving increasing recognition in the scientific community. His publications have been cited extensively, reflecting the impact of his work in artificial intelligence and healthcare.

He is actively involved in academic and professional service, serving as a reviewer for top-tier journals such as IEEE Transactions on Intelligent Vehicles, Robotics & Automation Letters, and Sensors. He is a member of IEEE, IEEE Robotics and Automation Society, IEEE Signal Processing Society, and the IEEE Computer Society.

Research Areas and Interests

  • Deep learning in robotics, electrical engineering and computer vision
  • AI-driven medical diagnostics, signal processing, and sensor-based data analysis
  • Edge computing, automation, and intelligent systems in healthcare and engineering

Qualifications

  • Doctor of Philosophy, Edith Cowan University, 2023.
  • Master of Science (Computer Science), Edith Cowan University, 2019.
  • Bachelor of Science in Electrical & Electronic Engineering, Bangladesh, 2010.

Research Outputs

2019

Conference Publications

  • Moniruzzaman, M., Islam, S., Lavery, P., Bennamoun, M. (2019). Faster R-CNN Based Deep Learning for Seagrass Detection from Underwater Digital Images. Proceedings of Digital Image Computing: Techniques and Application (Article number 8946048). IEEE. https://ro.ecu.edu.au/ecuworkspost2013/7020.

Research Projects

  • Artificial intelligent enhanced stethoscope to improve the diagnosis of Heart Valve Disease (HVD), Department of Health WA, Future Health Research & Innovation Fund - Innovation Fellowship, 2023 ‑ 2024, $147,192.
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