معرفی
Md Mahmudul Hasan is a Postdoctoral Fellow and casual academic in the Faculty of Engineering at The University of New South Wales (UNSW), specializing in Computer Science and Engineering. He holds a PhD in Computer Science & Engineering from UNSW Sydney, an MPhil in Biomedical Engineering & Applied Computer Science from Queensland University of Technology (QUT), and a Bachelor's degree in Electrical & Electronic Engineering from Khulna University of Engineering & Technology (KUET).
His educational background includes:
- Doctor of Philosophy (PhD) in Computer Science & Engineering from UNSW (2025), with research focusing on Artificial Intelligence, Machine Learning Engineering, Computer Engineering, and Biomedical Image Processing/Engineering
- Master of Philosophy (MPhil) in Biomedical Engineering from QUT (2021), with research in Signal Processing & Machine Learning Engineering
- Bachelor of Science in Electrical and Electronic Engineering from KUET, Bangladesh, with research in Signal Processing & Machine Learning Engineering
Hasan's research interests span artificial intelligence applications in medical contexts, with particular focus on medical imaging, EEG analysis, and diagnostic systems. His work bridges electrical engineering, biomedical engineering, and computer science to develop AI solutions for healthcare challenges including brain tumor detection, glaucoma diagnosis, and neurodegenerative disease assessment. He has extensive experience applying machine learning to physiological signals, particularly EEG data, for applications like emotion detection, drowsiness monitoring, and biometric identification.
His publication record demonstrates a strong trend toward explainable AI applications in medical diagnostics, with increasing focus on multimodal approaches that integrate various data sources for more accurate disease detection and monitoring. His work spans multiple medical domains including ophthalmology, neurology, and cardiology, with a consistent emphasis on developing practical, interpretable AI systems for clinical use.
His notable scientific achievements include:
- UNSW 3 Minutes Thesis (3-MT) Finalist 2022
- First Prize in UNSW School of CSE 3-MT Competition 2022
- Third Position at UNSW Faculty of Engineering 3-MT Competition 2022
- Australian Government Research Training Program (RTP) Scholarship
- University Dean's Award
- Joy Bangla Youth Award-2015
Hasan has received significant grant support including UNSW Tuition Fee Scholarship & Australian Government RTP Fees Offset (2021-2025), QUT Faculty Write-Up Scholarship (2021), and Australian Government RTP Scholarship (2019-2021). While at BAUET in Bangladesh, he supervised undergraduate thesis projects on EEG-based applications including emotion detection, wheelchair control, and smoker identification. His teaching responsibilities at UNSW include courses in Neural Networks and Deep Learning (COMP 9444) and Computer Vision (COMP 9517), where he conducts tutorials, lab demonstrations, and evaluates student projects.
