Md Mamunur Rahaman is a final-year PhD candidate in Computer Science and Engineering at the University of New South Wales (UNSW), Sydney. His research specializes in the intersection of engineering, biomedical science, and artificial intelligence, focusing on developing advanced image processing techniques and multimodal data integration approaches, including spatial transcriptomics and vision-language models, for computational pathology and computer-aided diagnostics.
His innovative work leverages sophisticated computational algorithms to enhance medical intervention through the analysis of histopathological and microscopic images. Mr. Rahaman has made significant contributions to the field with over 40 peer-reviewed journal and conference papers, achieving an H-index of 23 and accumulating over 3,000 citations on Google Scholar. Notably, six of his papers have been recognized as ESI Highly Cited Papers, ranking in the top 1% of the Engineering field, and his publication in Scientific Reports was ranked among the top 100 cancer research papers of 2023.
He recently completed a prestigious visiting fellowship at the Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University (December 2024 - April 2025), where he collaborated with Professor Anant Madabhushi's research group on advanced AI and machine vision techniques for computational pathology in cancer research.
Mr. 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 Northeastern University, he served as a research assistant in the Microscopic Image and Medical Image Analysis Group from 2021 to January 2022.
In addition to his doctoral research, he serves as a casual academic staff member at UNSW, tutoring courses including Computer Vision (COMP9517), Neural Networks and Deep Learning (COMP9444), and Artificial Intelligence (COMP3411) since May 2022. He also holds editorial positions, including Executive Editor of AI Medicine Journal and Review Editor for multiple Frontiers journals. Additionally, he serves as a reviewer for various prestigious journals across the biomedical engineering and artificial intelligence domains, including IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics, Scientific Reports (Nature), Computers in Biology and Medicine (Elsevier), and Artificial Intelligence Review, among others. His extensive peer review contributions span over 20 high-impact journals, demonstrating his recognized expertise in computational pathology, medical imaging, and artificial intelligence applications in healthcare.
Li R; Rahaman MM; Li X; Sun H; Yang J; Gao M; Grzegozek M; Jiang T; Huang X; Li C, 2025, 'An Extended Few-Shot Learning-Based Approach for Histopathological Image Classification of Pan-Cancer in the Digestive System', in , pp. 140 - 154, http://dx.doi.org/10.1007/978-981-96-0840-9_10
Book Chapters | 2025
Sun Y; Du T; Sun H; Xu J; Rahaman MM; Wang X; Huang X; Jiang T; Grzegorzek M; Xu N; Li C, 2025, 'RBMO-Att-Bi-LSTM: A Red-Billed Blue Magpie Optimiser-Self-attention Mechanism Based Optimisation of Bi-Directional Long- and Short-Term Memory Networks for Classification of COVID-19 CT Images', in , pp. 171 - 185, http://dx.doi.org/10.1007/978-981-96-0840-9_12
Book Chapters | 2025
Ye S; Du T; Kulwa F; Meng X; Rahaman MM; Grzegorzek M; Xu N; Jiang T; Sun H; Li C, 2025, 'RPE-Diff: A Relative Position Encoding Diffusion Model for Perirenal Fat Segmentation in Metabolic Syndrome', in , pp. 155 - 170, http://dx.doi.org/10.1007/978-981-96-0840-9_11
Book Chapters | 2025
Yuan L; Rahaman MM; Sun H; Li X; Grzegorzek M; Xu N; Li C, 2025, 'MRes-CNN: A Multi-branch Residual CNN for Colorectal Histopathological Image Classification', in , pp. 125 - 139, http://dx.doi.org/10.1007/978-981-96-0840-9_9
Du T; Jiang T; Li X; Rahaman MM; Grzegorzek M; Li C, 2025, 'Prediction of TP53 mutations across female reproductive system pan-cancers using deep multimodal PET/CT radiogenomics', Frontiers in Medicine, 12, http://dx.doi.org/10.3389/fmed.2025.1608652
Journal articles | 2025
Du T; Li C; Grzegozek M; Huang X; Rahaman M; Wang X; Sun H, 2025, 'PET/CT radiomics for non-invasive prediction of immunotherapy efficacy in cervical cancer', Journal of X Ray Science and Technology, 33, pp. 1081 - 1092, http://dx.doi.org/10.1177/08953996251367203
Journal articles | 2025
Han Y; Liu K; Yuan L; Rahaman M; Grzegorzek M; Sun H; Li C; Chen H, 2025, 'Channel-Gated Transformers with Affinity CAM for Weakly Supervised Multi-Class Brain Tumor Segmentation', IEEE Journal of Biomedical and Health Informatics, http://dx.doi.org/10.1109/JBHI.2025.3634736
Journal articles | 2025
Rahaman MM; Millar EKA; Meijering E, 2025, 'Generalized deep learning for histopathology image classification using supervised contrastive learning', Journal of Advanced Research, 75, pp. 389 - 404, http://dx.doi.org/10.1016/j.jare.2024.11.013
Journal articles | 2025
Rahaman MM; Millar EKA; Meijering E, 2025, 'Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images', IEEE Journal of Biomedical and Health Informatics, http://dx.doi.org/10.1109/JBHI.2025.3584802
Journal articles | 2025
Sun Y; Du T; Wang B; Rahaman MM; Wang X; Huang X; Jiang T; Grzegorzek M; Sun H; Xu J; Li C, 2025, 'COVID-19CT+: A public dataset of CT images for COVID-19 retrospective analysis', Journal of X Ray Science and Technology, 33, pp. 901 - 915, http://dx.doi.org/10.1177/08953996251332793
Journal articles | 2025
Yuan L; Chen Y; Rahaman M; Sun H; Chen H; Grzegorzek M; Li C; Li X, 2025, 'Dual-Level Imbalance Mitigation for Single-FoV Colorectal Histopathology Image Classification', IEEE Journal of Biomedical and Health Informatics, http://dx.doi.org/10.1109/JBHI.2025.3629064
Journal articles | 2024
Chen A; Li C; Rahaman MM; Yao Y; Chen H; Yang H; Zhao P; Hu W; Liu W; Zou S; Xu N; Grzegorzek M, 2024, 'Deep learning methods for noisy sperm image classification from convolutional neural network to visual transformer: a comprehensive comparative study', Intelligent Medicine, 4, pp. 114 - 127, http://dx.doi.org/10.1016/j.imed.2023.04.001
Journal articles | 2024
Chen H; Li X; Li C; Rahaman MM; Li X; Wu J; Sun H; Grzegorzek M; Li X, 2024, 'What can machine vision do for lymphatic histopathology image analysis: a comprehensive review', Artificial Intelligence Review, 57, http://dx.doi.org/10.1007/s10462-024-10701-w
Journal articles | 2024
Li R; Li X; Sun H; Yang J; Rahaman M; Grzegozek M; Jiang T; Huang X; Li C, 2024, 'Few-shot learning based histopathological image classification of colorectal cancer', Intelligent Medicine, 4, pp. 256 - 267, http://dx.doi.org/10.1016/j.imed.2024.05.003
Journal articles | 2024
Yu Y; Li X; Du T; Rahaman M; Grzegorzek MJ; Li C; Sun H, 2024, 'Increasing the accuracy and reproducibility of positron emission tomography radiomics for predicting pelvic lymph node metastasis in patients with cervical cancer using 3D local binary pattern-based texture features', Intelligent Medicine, 4, pp. 153 - 160, http://dx.doi.org/10.1016/j.imed.2024.03.001
Journal articles | 2023
Hu W; Li C; Rahaman MM; Chen H; Liu W; Yao Y; Sun H; Grzegorzek M; Li X, 2023, 'EBHI: A new Enteroscope Biopsy Histopathological H&E Image Dataset for image classification evaluation', Physica Medica, 107, http://dx.doi.org/10.1016/j.ejmp.2023.102534
Journal articles | 2023
Kulwa F; Li C; Grzegorzek M; Rahaman MM; Shirahama K; Kosov S, 2023, 'Segmentation of weakly visible environmental microorganism images using pair-wise deep learning features', Biomedical Signal Processing and Control, 79, http://dx.doi.org/10.1016/j.bspc.2022.104168
Journal articles | 2023
Ma P; Li C; Rahaman MM; Yao Y; Zhang J; Zou S; Zhao X; Grzegorzek M, 2023, 'A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches', Artificial Intelligence Review, 56, pp. 1627 - 1698, http://dx.doi.org/10.1007/s10462-022-10209-1
Journal articles | 2023
Rahaman MM; Millar EKA; Meijering E, 2023, 'Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning', Scientific Reports, 13, pp. 13604, http://dx.doi.org/10.1038/s41598-023-40219-0
Journal articles | 2023
Zhang J; Li C; Rahaman MM; Yao Y; Ma P; Zhang J; Zhao X; Jiang T; Grzegorzek M, 2023, 'A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements', Archives of Computational Methods in Engineering, 30, pp. 639 - 673, http://dx.doi.org/10.1007/s11831-022-09811-x
Journal articles | 2022
Chen A; Li C; Zou S; Rahaman MM; Yao Y; Chen H; Yang H; Zhao P; Hu W; Liu W; Grzegorzek M, 2022, 'SVIA dataset: A new dataset of microscopic videos and images for computer-aided sperm analysis', Biocybernetics and Biomedical Engineering, 42, pp. 204 - 214, http://dx.doi.org/10.1016/j.bbe.2021.12.010
Journal articles | 2022
Chen H; Li C; Li X; Rahaman MM; Hu W; Li Y; Liu W; Sun C; Sun H; Huang X; Grzegorzek M, 2022, 'IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach', Computers in Biology and Medicine, 143, http://dx.doi.org/10.1016/j.compbiomed.2022.105265
Journal articles | 2022
Chen H; Li C; Wang G; Li X; Mamunur Rahaman M; Sun H; Hu W; Li Y; Liu W; Sun C; Ai S; Grzegorzek M, 2022, 'GasHis-Transformer: A multi-scale visual transformer approach for gastric histopathological image detection', Pattern Recognition, 130, http://dx.doi.org/10.1016/j.patcog.2022.108827
Journal articles | 2022
Hu W; Li C; Li X; Rahaman MM; Ma J; Zhang Y; Chen H; Liu W; Sun C; Yao Y; Sun H; Grzegorzek M, 2022, 'GasHisSDB: A new gastric histopathology image dataset for computer aided diagnosis of gastric cancer', Computers in Biology and Medicine, 142, http://dx.doi.org/10.1016/j.compbiomed.2021.105207
Journal articles | 2022
Li X; Li C; Rahaman MM; Sun H; Li X; Wu J; Yao Y; Grzegorzek M, 2022, 'A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches', Artificial Intelligence Review, 55, pp. 4809 - 4878, http://dx.doi.org/10.1007/s10462-021-10121-0
Journal articles | 2022
Li Y; Li C; Li X; Wang K; Rahaman MM; Sun C; Chen H; Wu X; Zhang H; Wang Q, 2022, 'A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis', Archives of Computational Methods in Engineering, 29, pp. 609 - 639, http://dx.doi.org/10.1007/s11831-021-09591-w
Journal articles | 2022
Li Y; Wu X; Li C; Li X; Chen H; Sun C; Rahaman MM; Yao Y; Zhang Y; Jiang T, 2022, 'A hierarchical conditional random field-based attention mechanism approach for gastric histopathology image classification', Applied Intelligence, 52, pp. 9717 - 9738, http://dx.doi.org/10.1007/s10489-021-02886-2
Journal articles | 2022
Liu W; Li C; Rahaman MM; Jiang T; Sun H; Wu X; Hu W; Chen H; Sun C; Yao Y; Grzegorzek M, 2022, 'Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: From convolutional neural networks to visual transformers', Computers in Biology and Medicine, 141, http://dx.doi.org/10.1016/j.compbiomed.2021.105026
Journal articles | 2022
Liu W; Li C; Xu N; Jiang T; Rahaman MM; Sun H; Wu X; Hu W; Chen H; Sun C; Yao Y; Grzegorzek M, 2022, 'CVM-Cervix: A hybrid cervical Pap-smear image classification framework using CNN, visual transformer and multilayer perceptron', Pattern Recognition, 130, http://dx.doi.org/10.1016/j.patcog.2022.108829
Journal articles | 2022
Zhang J; Li C; Rahaman MM; Yao Y; Ma P; Zhang J; Zhao X; Jiang T; Grzegorzek M, 2022, 'A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches', Artificial Intelligence Review, 55, pp. 2875 - 2944, http://dx.doi.org/10.1007/s10462-021-10082-4
Journal articles | 2022
Zhang J; Zhao X; Jiang T; Rahaman MM; Yao Y; Lin YH; Zhang J; Pan A; Grzegorzek M; Li C, 2022, 'An Application of Pixel Interval Down-Sampling (PID) for Dense Tiny Microorganism Counting on Environmental Microorganism Images', Applied Sciences Switzerland, 12, http://dx.doi.org/10.3390/app12147314
Journal articles | 2022
Zhao P; Li C; Rahaman MM; Xu H; Ma P; Yang H; Sun H; Jiang T; Xu N; Grzegorzek M, 2022, 'EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification, and Detection Method Evaluation', Frontiers in Microbiology, 13, http://dx.doi.org/10.3389/fmicb.2022.829027
Journal articles | 2022
Zhao P; Li C; Rahaman MM; Xu H; Yang H; Sun H; Jiang T; Grzegorzek M, 2022, 'A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): From Convolutional Neural Networks to Visual Transformers', Frontiers in Microbiology, 13, http://dx.doi.org/10.3389/fmicb.2022.792166
Journal articles | 2021
Ai S; Li C; Li X; Jiang T; Grzegorzek M; Sun C; Rahaman MM; Zhang J; Yao Y; Li H, 2021, 'A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development', Biomed Research International, 2021, http://dx.doi.org/10.1155/2021/6671417
Journal articles | 2021
Li Z; Li C; Yao Y; Zhang J; Rahaman M; Xu H; Kulwa F; Lu B; Zhu X; Jiang T, 2021, 'EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks', Plos One, 16, http://dx.doi.org/10.1371/journal.pone.0250631
Journal articles | 2021
Rahaman MM; Li C; Yao Y; Kulwa F; Wu X; Li X; Wang Q, 2021, 'DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques', Computers in Biology and Medicine, 136, http://dx.doi.org/10.1016/j.compbiomed.2021.104649
Journal articles | 2020
Li X; Li C; Kulwa F; Rahaman MM; Zhao W; Wang X; Xue D; Yao Y; Cheng Y; Li J; Qi S; Jiang T, 2020, 'Foldover Features for Dynamic Object Behaviour Description in Microscopic Videos', IEEE Access, 8, pp. 114519 - 114540, http://dx.doi.org/10.1109/ACCESS.2020.3003993
Journal articles | 2020
Rahaman MM; Li C; Wu X; Yao Y; Hu Z; Jiang T; Li X; Qi S, 2020, 'A survey for cervical cytopathology image analysis using deep learning', IEEE Access, 8, pp. 61687 - 61710, http://dx.doi.org/10.1109/ACCESS.2020.2983186
Journal articles | 2020
Rahaman MM; Li C; Yao Y; Kulwa F; Rahman MA; Wang Q; Qi S; Kong F; Zhu X; Zhao X, 2020, 'Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches', Journal of X Ray Science and Technology, 28, pp. 821 - 839, http://dx.doi.org/10.3233/XST-200715
Journal articles | 2020
Sun C; Li C; Zhang J; Rahaman MM; Ai S; Chen H; Kulwa F; Li Y; Li X; Jiang T, 2020, 'Gastric histopathology image segmentation using a hierarchical conditional random field', Biocybernetics and Biomedical Engineering, 40, pp. 1535 - 1555, http://dx.doi.org/10.1016/j.bbe.2020.09.008
Journal articles | 2020
Xu H; Li C; Rahaman MM; Yao Y; Li Z; Zhang J; Kulwa F; Zhao X; Qi S; Teng Y, 2020, 'An enhanced framework of generative adversarial networks (EF-GANs) for environmental microorganism image augmentation with limited rotationinvariant training data', IEEE Access, 8, pp. 187455 - 187469, http://dx.doi.org/10.1109/ACCESS.2020.3031059
Journal articles | 2020
Xue D; Zhou X; Li C; Yao Y; Rahaman MM; Zhang J; Chen H; Zhang J; Qi S; Sun H, 2020, 'An Application of Transfer Learning and Ensemble Learning Techniques for Cervical Histopathology Image Classification', IEEE Access, 8, pp. 104603 - 104618, http://dx.doi.org/10.1109/ACCESS.2020.2999816
Journal articles | 2020
Zhou X; Li C; Rahaman MM; Yao Y; Ai S; Sun C; Wang Q; Zhang Y; Li M; Li X; Jiang T; Xue D; Qi S; Teng Y, 2020, 'A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks', IEEE Access, 8, pp. 90931 - 90956, http://dx.doi.org/10.1109/ACCESS.2020.2993788
Preprints | 2025
Rahaman MM; Millar EKA; Meijering E, 2025, Leveraging Vision-Language Embeddings for Zero-Shot Learning in
Histopathology Images, http://arxiv.org/abs/2503.10731v1
Conference Papers | 2024
Chen A; Fan FL; Zhang J; Rahaman MM; Li R; Tao J; Zeng T; Grzegorzek M; Li C, 2024, 'ACTIVE: A Deep Network for Sperm and Impurity Detection in Microscopic Videos', in Proceedings 2024 IEEE International Conference on Bioinformatics and Biomedicine Bibm 2024, pp. 5247 - 5256, http://dx.doi.org/10.1109/BIBM62325.2024.10822549
Conference Papers | 2024
Rahaman MM; Millar EKA; Meijering E, 2024, 'Histopathology Image Classification Using Supervised Contrastive Deep Learning', in Proceedings International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI56570.2024.10635260
Conference Papers | 2024
Yuan L; Rahaman M; Sun H; Li C; Gu Y; Jiang T; Grzegorzek M; Li X, 2024, 'A GAN-Based Data Augmentation Method for Mitigating Class Imbalance Problem in Histopathological Image Classification', in Proceedings 2024 IEEE International Conference on Bioinformatics and Biomedicine Bibm 2024, pp. 5327 - 5334, http://dx.doi.org/10.1109/BIBM62325.2024.10822517
Preprints | 2023
Chen A; Zhang J; Rahaman MM; Sun H; D. M; Zeng T; Grzegorzek M; Fan F-L; Li C, 2023, ACTIVE: A Deep Model for Sperm and Impurity Detection in Microscopic Videos, http://dx.doi.org/10.48550/arxiv.2301.06002
Preprints | 2023
Rahaman MM; Millar EKA; Meijering E, 2023, Breast Cancer Histopathology Image based Gene Expression Prediction
using Spatial Transcriptomics data and Deep Learning, http://dx.doi.org/10.1038/s41598-023-40219-0
Preprints | 2023
Rahaman MM; Millar EKA; Meijering E, 2023, Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning, http://dx.doi.org/10.21203/rs.3.rs-2983276/v1
Conference Papers | 2023
Zhang J; Zou S; Li C; Yao Y; Rahaman M; Qian W; Sun H; Grzegorzek M; Wang G, 2023, 'TOD-Net: Transformer-Based Neural Network for Tiny Object Detection in Sperm Microscopic Videos', in Proceedings International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI53787.2023.10230550
Preprints | 2022
Chen H; Li C; Li X; Rahaman MM; Hu W; Li Y; Liu W; Sun C; Sun H; Huang X; Grzegorzek M, 2022, IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach, http://dx.doi.org/10.48550/arxiv.2206.03368
Preprints | 2022
Hu W; Li C; Li X; Rahaman MM; Zhang Y; Chen H; Liu W; Yao Y; Sun H; Xu N; Huang X; Grzegorze M, 2022, EBHI:A New Enteroscope Biopsy Histopathological H&E Image Dataset for Image Classification Evaluation, http://dx.doi.org/10.48550/arxiv.2202.08552
Preprints | 2022
Kulwa F; Li C; Grzegorzek M; Rahaman MM; Shirahama K; Kosov S, 2022, Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features, http://dx.doi.org/10.48550/arxiv.2208.14957
Preprints | 2022
Li X; Chen H; Li C; Rahaman MM; Li X; Wu J; Li X; Sun H; Grzegorzek M, 2022, What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review, http://dx.doi.org/10.48550/arxiv.2201.08550
Preprints | 2022
Liu W; Li C; Xu N; Jiang T; Rahaman MM; Sun H; Wu X; Hu W; Chen H; Sun C; Yao Y; Grzegorzek M, 2022, CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron, http://dx.doi.org/10.48550/arxiv.2206.00971
Preprints | 2022
Zhang J; Li C; Rahaman MM; Yao Y; Ma P; Zhang J; Zhao X; Jiang T; Grzegorzek M, 2022, A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements, http://dx.doi.org/10.48550/arxiv.2202.09020
Preprints | 2022
Zhang J; Zhao X; Jiang T; Rahaman MM; Yao Y; Lin Y-H; Zhang J; Pan A; Grzegorzek M; Li C, 2022, An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism images, http://dx.doi.org/10.48550/arxiv.2204.01341
Preprints | 2021
Chen H; Li C; Wang G; Li X; Rahaman M; Sun H; Hu W; Li Y; Liu W; Sun C; Ai S; Grzegorzek M, 2021, GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection, http://dx.doi.org/10.48550/arxiv.2104.14528
Preprints | 2021
Hu W; Li C; Li X; Rahaman MM; Ma J; Zhang Y; Chen H; Liu W; Sun C; Yao Y; Sun H; Grzegorzek M, 2021, GasHisSDB: A New Gastric Histopathology Image Dataset for Computer Aided Diagnosis of Gastric Cancer, http://dx.doi.org/10.48550/arxiv.2106.02473
Preprints | 2021
Li C; Li X; Rahaman M; Li X; Sun H; Zhang H; Zhang Y; Li X; Wu J; Yao Y; Grzegorzek M, 2021, A Comprehensive Review of Computer-aided Whole-slide Image Analysis:
from Datasets to Feature Extraction, Segmentation, Classification, and
Detection Approaches, http://arxiv.org/abs/2102.10553v1
Conference Papers | 2021
Li Y; Wu X; Li C; Sun C; Li X; Rahaman M; Zhang Y, 2021, 'Intelligent Gastric Histopathology Image Classification Using Hierarchical Conditional Random Field based Attention Mechanism', in ACM International Conference Proceeding Series, pp. 330 - 335, http://dx.doi.org/10.1145/3457682.3457733
Preprints | 2021
Li Y; Wu X; Li C; Sun C; Rahaman M; Chen H; Yao Y; Li X; Zhang Y; Jiang T, 2021, A Hierarchical Conditional Random Field-based Attention Mechanism
Approach for Gastric Histopathology Image Classification, http://arxiv.org/abs/2102.10499v2
Preprints | 2021
Li Z; Li C; Yao Y; Zhang J; Rahaman MM; Xu H; Kulwa F; Lu B; Zhu X; Jiang T, 2021, EMDS-5: Environmental Microorganism Image Dataset Fifth Version for
Multiple Image Analysis Tasks, http://dx.doi.org/10.1371/journal.pone.0250631
Preprints | 2021
Ma P; Li C; Rahaman MM; Yao Y; Zhang J; Zou S; Zhao X; Grzegorzek M, 2021, A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approaches, http://dx.doi.org/10.48550/arxiv.2105.03148
Preprints | 2021
Rahaman MM; Li C; Yao Y; Kulwa F; Wu X; Li X; Wang Q, 2021, DeepCervix: A Deep Learning-based Framework for the Classification of
Cervical Cells Using Hybrid Deep Feature Fusion Techniques, http://dx.doi.org/10.1016/j.compbiomed.2021.104649
Preprints | 2021
Zhang J; Li C; Rahaman MM; Yao Y; Ma P; Zhang J; Zhao X; Jiang T; Grzegorzek M, 2021, A Comprehensive Review of Image Analysis Methods for Microorganism
Counting: From Classical Image Processing to Deep Learning Approaches, http://arxiv.org/abs/2103.13625v4
Preprints | 2021
Zhao P; Li C; Rahaman MM; Xu H; Ma P; Yang H; Sun H; Jiang T; Xu N; Grzegorzek M, 2021, EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation, http://dx.doi.org/10.48550/arxiv.2112.07111
Preprints | 2021
Zhao P; Li C; Rahaman MM; Xu H; Yang H; Sun H; Jiang T; Grzegorzek M, 2021, A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers, http://dx.doi.org/10.48550/arxiv.2107.07699
Preprints | 2020
Li Y; Li C; Li X; Wang K; Rahaman MM; Sun C; Chen H; Wu X; Zhang H; Wang Q, 2020, A Comprehensive Review for MRF and CRF Approaches in Pathology Image
Analysis, http://dx.doi.org/10.1007/s11831-021-09591-w
Preprints | 2020
Zhou X; Li C; Rahaman MM; Yao Y; Ai S; Sun C; Li X; Wang Q; Jiang T, 2020, A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks, http://dx.doi.org/10.48550/arxiv.2003.12255
Conference Papers | 2018
Rahaman MM; Chowdhury A; Islam M; Rahman MM, 2018, 'CZTS based thin film solar cell: An investigation into the influence of dark current on cell performance', in 2018 Joint 7th International Conference on Informatics Electronics and Vision and 2nd International Conference on Imaging Vision and Pattern Recognition Iciev Ivpr 2018, pp. 87 - 92, http://dx.doi.org/10.1109/ICIEV.2018.8641013
Professional Memberships
Professional Member, Association for Computing Machinery (ACM), 2021 - Present
IEEE Graduate Student 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
Editorial Board Memberships
Associate Editor, Frontiers in Oncology—Breast Cancer, 2025 – Present
Executive Editor, AI Medicine Journal, Scilight Press, 2024 – Present
Review Editor for Machine Learning and Artificial Intelligence:
Frontiers in Big Data, 2022 – Present
Frontiers in Artificial Intelligence, 2022 – Present
Review Editor for Image Retrieval:
Frontiers in Imaging, 2022 – Present
Reviewer:
IEEE Transactions on Medical Imaging, 2022 - Present
Applied Artificial Intelligence, 2022 - Present
IEEE Journal of Biomedical and Health Informatics, 2022 - Present
Interdisciplinary Sciences: Computational Life Sciences, 2021 - Present
Biomedical Signal Processing and Control (Elsevier), 2022 - Present
BMC Cancer (Springer Nature), 2022 - Present
Informatics in Medicine Unlocked (Elsevier), 2022 - Present
BMC Medical Imaging (Springer Nature), 2021 - Present
Computers in Biology and Medicine (Elsevier), 2022 - Present
IEEE Access, 2020 – Present
Diagnostics (MDPI), 2022 - Present
Expert Systems with Applications, 2022 - Present
Heliyon, 2022 – Present
Artificial Intelligence Review, 2021 - Present
Journal of Personalized Medicine (MDPI), 2022 - Present
Journal of Big Data, 2021 - Present
Sensors (MDPI), 2022 - Present
Technology in Cancer Research & Treatment, 2021 - Present
World Journal of Surgical Oncology (Springer Nature), 2021 - Present
My Research Supervision
My Teaching
I have been actively involved in tutoring and mentoring students across several key courses within the School of Computer Science and Engineering. My teaching philosophy is centered on fostering a deep understanding of core concepts, encouraging practical application, and inspiring innovation among students.
