Dr David Olayemi Alebiosu

Dr David Olayemi Alebiosu

  • Lecturer
Department of Data Science and Artificial Intelligence
Google Scholar ORCID ResearchGate
SDGs Focus
Good Health and Well Being
Life On Land

Biography

Dr David holds a Bachelor's in Computer Science from Binary University. He obtained his Master of Philosophy in Information Technology from the prestigious Monash University. He also completed his PhD in Information Technology from the same University. Dr David has been actively involved in teaching and researching for several years. He has developed many innovative ways to process medical images, such as X-ray and CT scan segmentation and classification. Some of his research outputs have been published in peer-reviewed journals and conferences. Dr David's areas of specialization include artificial intelligence, machine learning, deep learning, medical image processing, and pattern recognition. Dr David delights in delivering engaging lectures and conducting qualitative research with outstanding outputs to improve the field of artificial intelligence and Computer Science.

Academic & Professional Qualifications

  • Doctor of Philosophy in Information Technology, Monash University
  • Master of Philosophy in Information Technology, Monash University
  • Bachelor of Science in Computer Science, Binary University, Malaysia

Research Interests

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Medical imaging

Teaching Areas

  • Artificial Intelligence
  • Data Science
  • Software Engineering
  • Database Management Systems

Courses Taught

  • Object-orineted programming
  • Python
  • Concurrent Programming
  • Database Management Systems

Notable Publications

  1. Alebiosu DO, A. Dharmaratne, CH Lim, “Enhanced 3D-OTSU Algorithm for Robust Tuberculosis and COVID-19 CT Scans Segmentation”, IEEE Conference on Visual Communications and Image Processing (VCIP), 2023.
  2. Alebiosu DO, A. Dharmaratne, CH Lim, “Improving Tuberculosis Severity Assessment in Computed Tomography Images Using Novel DAvoU-Net Segmentation Technique and Deep Learning Framework”, Journal of Expert Systems with Applications (2023).
  3. Alebiosu DO, A. Dharmaratne, MF Pasha, “Deep Learning and Late Fusion Technique in Medical X-ray Image Classification”, 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2020
  4. Alebiosu DO, MF Pasha, A Dharmaratne, “Medical Image Classification: A Comparison of Deep Pre-trained Neural Networks”, 2019 IEEE Student Conference on Research and Development (SCOReD), Perak, Malaysia- (SCOPUS Cited).
  5. Zare MR, Alebiosu DO, Lee SL, "Comparison of handcrafted features and deep learning in the classification of medical X-ray images", 4th International Conference on Information Retrieval and Knowledge Management, 2018 (SCOPUS Cited).
  6. Alebiosu DO, Zare MR, MF Pasha, “Medical Image Classification: A Comparison of various Handcrafted Features ", International Journal of Advances in Soft Computing and Its Applications (2018) - (SCOPUS Cited).