Dr. Mamunur Rahaman is a researcher at the intersection of biomedical science and artificial intelligence, developing computational methods for healthcare with a focus on multimodal medical AI and computational pathology. He completed his PhD in Computer Science and Engineering at UNSW Sydney in 2025, supervised by Professor Erik Meijering, Professor Anant Madabhushi, and Associate Professor Ewan Millar. His research integrates histopathology with complementary modalities, including radiology, molecular and clinical data, spatial transcriptomics, and vision-language models, to build robust and clinically meaningful models for diagnosis, prognosis, and treatment stratification.​

Dr. Rahaman has contributed to over 40 peer-reviewed journal and conference papers, achieving an H-index of 23 and accumulating over 3,300 citations on Google Scholar. His work has received international recognition, including four papers named ESI Highly Cited Papers ranking in the top 1% of the Engineering field, and a Scientific Reports publication ranked among the top 100 cancer research papers of 2023.​

He held a Visiting Fellowship at the Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University (December 2024–April 2025), collaborating with Professor Anant Madabhushi's research group on advanced AI and machine vision techniques for computational pathology in cancer research. He also served as a Visiting Researcher at the Technical University of Munich (October 2025), where he delivered a seminar on multimodal pathology AI and engaged with the Schüffler Lab's research. Currently, he serves as a Postdoctoral Writing Fellow at UNSW (November 2025–January 2026), supporting research writing and publication outcomes.​

Dr. Rahaman earned his Bachelor of Science in Electrical and Electronic Engineering with High Distinction from BRAC University, Bangladesh, and his Master of Biomedical Engineering with Highest Distinction from Northeastern University, China. At UNSW, he has served as casual academic staff tutoring courses including Computer Vision (COMP9517), Neural Networks and Deep Learning (COMP9444), and Artificial Intelligence (COMP9814) since May 2022. He also contributes to the research community through editorial roles, including Associate Editor at Frontiers in Oncology—Breast Cancer and Executive Editor at AI Medicine Journal. His extensive peer review contributions span over 20 high-impact journals, including IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics, Scientific Reports, and Computers in Biology and Medicine, demonstrating his recognized expertise in computational pathology, medical imaging, and artificial intelligence applications in healthcare.