I am a final-year Ph.D. researcher in Artificial Intelligence (AI) at James Cook University (JCU) in the Department of Information Technology, supervised by Dr. Euijoon Ahn. My research focuses on computer vision, generative AI, and self-supervised learning for medical imaging. I aim to develop robust and generalizable AI systems by integrating deep learning and generative modeling techniques to improve medical image analysis and clinical decision-making.
Prior to joining JCU, I worked as a Research Assistant at Inje University, South Korea, where I collaborated with hospitals and industry partners on applied AI research. I also completed my M.S. at Inje University under the supervision of Prof. Hee-Cheol Kim. In addition, I have industry experience working with startups on computer vision applications, including real-time face-shape identification and baseball speed detection systems. My research interests include AI, deep learning, computer vision, medical imaging, foundation models, self-supervised learning, diffusion model and GenAI. I have worked with X-rays, histopathology, MRI, and ultrasound imaging, focusing on developing practical AI solutions for healthcare.
Additionally, I serve as a Topic Coordinator for Frontiers in Digital Health and actively contribute as a reviewer for leading venues, including IEEE TMI, MICCAI, and journals from major publishers such as IEEE and MDPI.
Artificial Intelligence, Machine Learning, Deep Learning, Weakly Supervised Learning, Self-Supervised Learning, Foundation Models, Computer Vision, Large Language Models (LLMs), Vision-Language Models (VLMs), LLMs with Retrieval-Augmented Generation (RAG), Agentic AI, Diffusion Models, Generative AI (GenAI).
Technical and Development Skills:
Programming & Frameworks: Python, PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, OpenCV, CUDA
AI & ML Development: Image Classification, Object Detection, Image Segmentation, YOLO, Faster R-CNN, SSD, ResNet, U-Net, Multimodal Models
Generative & LLM Tools: GPT, OpenAI API, LangChain/LangGraph, HuggingFace, RAG
Deployment & MLOps: Linux Server, Flask, REST APIs, Vector Databases, AWS (ECS, SageMaker), Cloud Platforms, Model Optimization, Model Deployment
Data Processing & Augmentation: Data Preprocessing, Augmentation Pipelines
AI in Healthcare – Cloud-Based
Conducted classification and segmentation tasks on medical imaging using AWS (EC2, S3, Jupyter), managing large datasets and deploying AI workflows on the cloud.
Crocodile Detection – Cairns, Australia
Casual staff member on a QLD government project, performing video analysis and labeling to detect crocodiles in wild environments. Worked with large-scale video datasets to improve wildlife monitoring.
Diffusion-Based Medical Image Generation
Developed deep generative diffusion models to synthesize medical images for classification, segmentation, and diagnosis using self-supervised learning techniques.
Smart Computing Laboratory, Inje University
AI Research Assistant: Working on various datasets such as Image data, sensor data, tabular data, etc. using state-of-the-art AI algorithms.
Industry Experience – Computer Vision Applications
I have worked with startups developing computer vision solutions, including real-time face-shape recognition and baseball speed detection systems.
▪︎ James Cook University, Ph.D. in Information Technology ( Medical Imaging) (advisor: Dr. Euijoon Ahn) / QLD, Cairns , Australia / OnGoing
▪︎ Inje University, MS in Artificial intelligence in Healthcare ( Advisor - Prof. Hee-Cheol Kim / Gimhae, South Korea / Febuary 2023
▪︎ COMSATS University , B.S in Electrical and Computer Engineering, Abbottabad Pakistan/ Jan 2018
Scholarship For Master Degree
2021 to 2023 | BK21 Research Scholarship, Inje University South Korea (busan, KR)
Scholarship For Ph.D. Degree
2023 to 2027 | HDR Scholarship, James Cook University Australia (QLD Cairns, AUS)
Research Grants
2023 | Received Conference Grants 1200A$, James Cook University Australia (QLD Cairns, AUS)
Research Grants
2025 | Received Conference Grants 2800A$James Cook University Australia (QLD Cairns, AUS)
C: conference, W: workshop, J: journal, P: preprint / * equal contribution
[P] Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review.
Mr Abdullah, Tao Huang, Ickjai Lee, Euijoon Ahn,
Paper, 2025 May
[C] High-Resolution Histopathology Whole Slide Image Generation Using Wavelet Diffusion Model.
Mr Abdullah, Tao Huang, Ickjai Lee, Euijoon Ahn
Paper, 2025 April
Mr Abdullah*, Sikandar Ali *, Armand Poupi, Hee-Cheol Kim
paper / poster , 2023
Ali Athar, Md Ariful Islam Mozumder, Mr Abdullah, Hee-Cheol Kim
Paper, 2024 October
[J] Computer Vision Based Deep Learning Approach for the Detection and Classification of Algae Species Using Microscopic Images
Mr Abdullah, Sikandar Ali , Zia ullah, Hussain Ali, Athar Ali, Hee-Cheol Kim
paper / poster
[J]. Detection of COVID-19 in X-Ray Images using Densely Connected Squeeze Convolutional Neural Network (DCSCNN): Focusing on Interpretability and Explainability of the Black Box Model". Journal of Biomedical and Health Informatics
Sikandar Ali, Ali Hussain, Subrata. B, Athar Ali, Mr Abdullah, and Hee-Cheol Kim.
[C] Multiclass-Classification of Algae using Dc-GAN and Transfer Learning. In 2022 2nd International Conference on Image Processing and Robotics (ICIPRob) (pp. 1-6). IEEE.
Mr.Abdullah, Khan, Z., Mumtaz, W., Mumtaz, A.S., Bhattacharjee, S. and Kim, H.C., 2022, March.
[J]. Activity Detection for the Wellbeing of Dogs Using Wearable Sensors Based on Deep Learning. IEEE Access, 10, pp.53153-53163.
Hussain, A., Ali, S. Abdullah, and Kim, H.C., 2022.
[C]. Hybrid Based Model Face Shape Classification Using Ensemble Method for Hairstyle Recommender System. In Proceedings of 2nd International Conference on Smart Computing and Cyber Security: Strategic Foresight, Security Challenges and Innovation (SMARTCYBER 2021) (p. 61). Springer Nature.
Mr. Abdullah, A.H.,
[C]. Classification of Algae Plant Using Deep Learning. In INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING (Vol. 13, No. 1, pp. 8-12).
Mr. Abdullah, Sikandar, A., Hussain, A., Athar, A., Mohsin, M. and Kim, H.C., 2022, January.
Mr Abdullah, Mahsoom Ali Shah, Hee-Cheol Kim, 2024 Sep
MA5832: Data Mining and Machine Learning (Level 5; ON, 2023)
MA5831: SASS and Data Management (Level 5; Face-To-Face, 2024)
MA5851: Data Science Master Class-II ( Face-To-Face, 2024)
MA5840: Data Science and Decision Making (Face-To-Face, 2025 )
MA5832/MA5852: Neural Network and Deep Learning using (AWS) (Face-To-Face, 2025)
Leadership & Service
Treasurer, Postgraduate Society, JCU Cairns (2025–2026) – Managed society activities and budgets.
Graduate Student Mentor – Guiding and supporting Master’s and Ph.D. students.
JCU Community Garden Volunteer (since March 2024) – Actively contributing to campus sustainability initiatives.
Editorial & Reviewing Work
Guest Editor – Advances in Artificial Intelligence Transforming the Medical and Healthcare Sectors.
Reviewer – Evaluating submissions for prestigious journals, including IEEE-TMI, MICCAI, and IEEE Access
European Society of Pathology Presentation Certificate .
Certification of Presentation International Conference on Ultrasound and Radiology (ICUR-24).
James Cook University Respectful Relationship certificate.
Certification on Machine Learning Provided by Stanford | Online).
Certification IMPACT10x Cohort 26 JCU.
Certification on Python for Data Science, Ai & Developer).
Certification Of Appreciation From Smart Computing Lab (SCL) Inje University South Korea.
Certification on Deeplearning AI.
I am honored to mentor four collaborative projects between XUT and JCU honor students for their final year projects:
Huayu Xie: Developing a model for brain tumor segmentation utilizing a UNET architecture enhanced with an attention mechanism.
Zixuan Hou: Implementing a deep neural network based on multi-head attention for the detection of cervical spine fractures from CT scans.
Linshen Han: Creating a text-to-image generative model for dermoscopy images.
Haodong Zhang: Automating the 3D segmentation of kidneys and tumors.