Md Mamunur Rahaman, MEng, PhD

Research Fellow · Macquarie University – Australian Institute of Health Innovation (AIHI), Sydney, Australia

H-Index

3,500+

Citations

40+

Publications

ESI Highly Cited

Research Interests:

Computational Pathology Spatial Transcriptomics Vision–Language Models Multimodal Medical AI Cancer Prognosis Deep Learning Histopathology Analysis

Welcome

Hello and welcome to my website! I am a Research Fellow at the Australian Institute of Health Innovation (AIHI), Macquarie University, where I work at the intersection of artificial intelligence, computational pathology, and translational biomedical research. My research focuses on developing clinically relevant multimodal AI methods that integrate histopathology with molecular, clinical, and other complementary data sources to improve cancer diagnosis, prognostic assessment, and treatment stratification.

I completed my PhD in Computer Science and Engineering at UNSW Sydney in January 2026, supervised by Professor Erik Meijering, Professor Anant Madabhushi, and Associate Professor Ewan Millar. My work spans deep learning for histopathology image analysis, spatial transcriptomics-guided modeling, vision-language learning, and multimodal foundation-model approaches for data-efficient and zero-shot medical AI.

I have authored over 40 peer-reviewed journal and conference papers, with an H-index of 25 and more than 3,500 citations on Google Scholar. My work has received international recognition, including four ESI Highly Cited Papers and a Scientific Reports publication ranked among the top 100 cancer research papers of 2023. In 2025, I was recognised by ScholarGPS as a Highly Ranked Scholar (Prior Five Years) in Histopathology, placing in the top 0.05% of scholars worldwide for productivity, impact, and quality of scholarly work.

My academic appointments and research visits include a Visiting Fellowship at the Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University (Dec 2024–Apr 2025), a Visiting Researcher appointment at the Technical University of Munich (Oct 2025), and a Postdoctoral Writing Fellowship at UNSW Sydney (Nov 2025–Jan 2026). These roles supported collaborations in computational pathology, multimodal AI, and translational cancer research.

In my current role at Macquarie University, I am advancing AI-driven research in computational pathology, spatial transcriptomics, and precision oncology. My ongoing and upcoming research also includes work on motor neurone disease (MND) involving gene data, extending my translational AI research toward data-driven neurological disease analysis.

I also continue to work as a casual academic at UNSW Sydney, contributing to teaching and academic activities across artificial intelligence, computer vision, and deep learning courses in the School of Computer Science and Engineering since 2022, including Computer Vision (COMP9517), Neural Networks and Deep Learning (COMP9444), and Artificial Intelligence (COMP9814). More broadly, I contribute to the research community through editorial service, topic-editing activities, and peer review for leading journals in medical imaging, biomedical AI, and computational pathology.

I earned a BSc in Electrical and Electronic Engineering (High Distinction) from BRAC University, Bangladesh, and a Master of Biomedical Engineering (MEng, Highest Distinction) from Northeastern University, China.

News

Mar 2026 Appointed Research Fellow at the Australian Institute of Health Innovation (AIHI), Macquarie University, Sydney, Australia.
Jan 2026 Abstract accepted for Oral Presentation at the ASCO Annual Meeting 2026 (Chicago, IL): spatial transcriptomics-guided pathology model validated on the CHAARTED clinical trial for prostate cancer treatment stratification.
Jan 2026 Abstract accepted for presentation at the ASCO Annual Meeting 2026 (Chicago, IL): spatial transcriptomics-guided pathology model validated on the NRG/RTOG 0521 clinical trial for prostate cancer treatment stratification.
Jan 2026 Successfully completed PhD in Computer Science and Engineering at UNSW Sydney. Thesis: Advancing Computational Pathology with Multimodal Deep Learning.
Dec 2025 Oral Presentation at NeurIPS 2025, San Diego, USA — PathDFM: Pathology Distillation Foundation Model for Multi-Scale WSI Analysis. Selected as a top-performing submission in the SLC-PFM challenge track.
Nov 2025 Appointed Postdoctoral Writing Fellow (Research-only) at UNSW Sydney (Nov 2025–Jan 2026), leading high-impact multimodal AI manuscript submissions.
Oct 2025 Visiting Researcher at Technical University of Munich (Schüffler Lab — AI for Pathology); delivered an invited seminar on multimodal pathology AI.
Oct 2025 Invited Speaker at the Datasets through the Looking-Glass webinar, IT University of Copenhagen, Denmark.
Sep 2025 Served as Workshop Chair at MVIPIT 2025 — Workshop: Few-shot and Incremental Learning for Data-Efficient AI, Shenyang, China.
2025 Honored by ScholarGPS as a Highly Ranked Scholar (Prior Five Years) in Histopathology — top 0.05% of scholars worldwide for productivity, impact, and quality of scholarly work.
2025 Received the Arc PGC Research Candidate Award (Faculty of Engineering), UNSW Postgraduate Council, recognised for above-and-beyond contribution to the HDR experience at UNSW.
Apr 2025 Completed Visiting Fellowship at the Madabhushi Lab, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, USA (Dec 2024–Apr 2025).
2024 Selected as a DAAD AInet Fellow (Postdoc-NeT-AI – AI for Science).

Publications

* First / corresponding author ESI Highly Cited Top 1% Engineering Top 100 Cancer Scientific Reports 2023

Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images

Rahaman MM*, Millar EKA, Meijering E

IEEE Journal of Biomedical and Health Informatics, 30, pp. 539–550, 2026 DOI
PET/CT Radiomics for Non-Invasive Prediction of Immunotherapy Efficacy in Cervical Cancer

Du T, Li C, Grzegozek M, Huang X, Rahaman M, Wang X, Sun H

Journal of X-Ray Science and Technology, 33, pp. 1081–1092, 2025 DOI
Prediction of TP53 Mutations across Female Reproductive System Pan-Cancers Using Deep Multimodal PET/CT Radiogenomics

Du T, Jiang T, Li X, Rahaman MM, Grzegorzek M, Li C

Frontiers in Medicine, 12, 2025 DOI
COVID-19CT+: A Public Dataset of CT Images for COVID-19 Retrospective Analysis

Sun Y, Du T, Wang B, Rahaman MM, Wang X, Huang X, Jiang T, Grzegorzek M, Sun H, Xu J, Li C

Journal of X-Ray Science and Technology, 33, pp. 901–915, 2025 DOI
Generalized Deep Learning for Histopathology Image Classification Using Supervised Contrastive Learning

Rahaman MM*, Millar EKA, Meijering E

Journal of Advanced Research, 75, pp. 389–404, 2025 DOI
Channel-Gated Transformers with Affinity CAM for Weakly Supervised Multi-Class Brain Tumor Segmentation

Han Y, Liu K, Yuan L, Rahaman M, Grzegorzek M, Sun H, Li C, Chen H

IEEE Journal of Biomedical and Health Informatics, 2025 DOI
Dual-Level Imbalance Mitigation for Single-FoV Colorectal Histopathology Image Classification

Yuan L, Chen Y, Rahaman M, Sun H, Chen H, Grzegorzek M, Li C, Li X

IEEE Journal of Biomedical and Health Informatics, 2025 DOI
What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review

Chen H, Li X, Li C, Rahaman MM, Li X, Wu J, Sun H, Grzegorzek M, Li X

Artificial Intelligence Review, 57, 2024 DOI
Breast Cancer Histopathology Image-Based Gene Expression Prediction Using Spatial Transcriptomics Data and Deep Learning ESI Highly Cited Top 100 Cancer

Rahaman MM*, Millar EKA, Meijering E

Scientific Reports, 13, pp. 13604, 2023 DOI
EBHI: A New Enteroscope Biopsy Histopathological H&E Image Dataset for Image Classification Evaluation

Hu W, Li C, Rahaman MM, Chen H, Liu W, Yao Y, Sun H, Grzegorzek M, Li X

Physica Medica, 107, 2023 DOI

View full publication list → | Google Scholar Profile →

Honors & Awards

2025 ScholarGPS Highly Ranked Scholar (Prior Five Years) — Specialty: Histopathology; top 0.05% of scholars worldwide for productivity, impact, and quality of scholarly work.
2025 Arc PGC Research Candidate Award (Faculty of Engineering), UNSW Postgraduate Council — recognised for above-and-beyond contribution to the HDR experience.
2025 DAAD AInet Research Visit Funding — Travel and subsistence support for a short-term visit to TUM, Munich, Germany.
2024 DAAD AInet Fellow (Postdoc-NeT-AI – AI for Science).
2024 Certificate to attend ISBI 2024, Athens, Greece.
2022–2025 UNSW University International Postgraduate Award (UIPA).
2022– Four papers recognised as ESI Highly Cited Papers — each entering the top 1% of the Engineering field.
2023 Publication in Scientific Reports ranked among the top 100 cancer research papers of 2023.
2022 Funding to attend the DICTA Conference 2022, Sydney.
2019–2020 Northeastern University Outstanding International Student Award (academic performance 2018–2019 & 2019–2020).
2018–2021 Chinese Government Scholarship.
2017 Graduated with High Distinction in Electrical & Electronic Engineering, BRAC University; performance-based scholarship and Dean’s certificates.

Academic Service

Editorial Roles

Topic Editor, MDPI Topic: Artificial Intelligence in Computational Pathology for Cancer Diagnosis (submissions open), 2026 – Present
Associate Editor, Frontiers in Oncology — Breast Cancer section, 2025 – Present
Executive Editor, AI Medicine Journal, Scilight Press, 2024 – Present
Review Editor, Frontiers in Big Data & Frontiers in Artificial Intelligence, 2022 – Present
Review Editor, Frontiers in Imaging, 2022 – Present

Reviewer

Active reviewer for 20+ journals including: IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics, IEEE Access, Scientific Reports, Computers in Biology and Medicine, Artificial Intelligence Review, Expert Systems with Applications, BMC Cancer, Biomedical Signal Processing and Control, Applied Artificial Intelligence, among others.

Conference Organisation

Workshop Chair, MVIPIT 2025 — Workshop 9: “Few-shot and Incremental Learning for Data-Efficient AI”, 27–29 Sep 2025, Shenyang, China.

Society Membership

IEEE Member, Region 10 (Asia and Pacific), New South Wales Section, 2024 – Present
Member, IEEE Engineering in Medicine and Biology Society, 2024 – Present
Member, IEEE Young Professionals, 2024 – Present
Member, Association for Computing Machinery (ACM), 2021 – Present

Topic Editor – Call for Submissions

Artificial Intelligence in Computational Pathology for Cancer Diagnosis

Topic Editor · MDPI Topics

I am serving as a Topic Editor for the MDPI Topic Artificial Intelligence in Computational Pathology for Cancer Diagnosis. The Topic is currently accepting submissions and welcomes original research articles and reviews on AI-driven cancer diagnosis, computational biomarker discovery, prognostic and predictive modeling, tumor microenvironment analysis, explainable AI, foundation models, and multimodal integration of pathology, genomics, and clinical data.

Participating journals include Cancers (IF 4.4), Current Oncology (IF 3.4), and Diagnostics (IF 3.3). Full scope, keywords, and submission details are available on the official Topic page.

View Topic and submission details →

Visitors

Visitor locations tracked via ClustrMaps. Click the map to view detailed analytics.

View full visitor analytics →