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. 

Research Interests:

• 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

• HPC & Computing: Ubuntu/Linux, GPU computing, CUDA environments, SLURM job scheduling, HPC clusters (JCU Bunya and UQ), Conda, model optimisation.

• 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: Hugging Face, GPT, OpenAI API, LangChain, Flask, REST APIs, AWS and reproducible ML workflows

• Data Processing & Augmentation: Data Preprocessing, Augmentation Pipelines

Work Experience:

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 for cat activity detection, tabular data, etc. using state-of-the-art AI algorithms.

Industry Experience – Computer Vision Applications  

• Worked with startups developing computer vision solutions, including real-time face-shape recognition and baseball speed detection systems.

      Brain–Computer Interface (BCI) and EEG Signal Processing 

• . Developed a prototype brain–computer interface (BCI) project involving EEG signal acquisition using a headset with scalp electrodes, signal preprocessing in LabVIEW, and Bluetooth communication with an Arduino to control a small motorised car. The project explored the concept of using brain signals to control assistive mobility devices, such as wheelchairs.

Education:

▪︎ 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

Honors & Awards:

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)

Teaching

• 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