Dr. Fawad Asadi is an Assistant Professor at CMKL University with expertise in artificial intelligence, computer science education, and medical image analysis. His research focuses on applying deep learning and machine learning techniques to medical imaging, computer vision, and neuroscience, with the goal of developing intelligent systems that support healthcare and scientific discovery.

Prior to joining CMKL University, Dr. Asadi accumulated over six years of teaching experience across international schools and higher education institutions in Thailand.

• D.Eng., Biomedical Engineering in Artificial Intelligence, Rangsit University, Thailand
• B.Eng., Electrical Engineering, Taibah University, Saudi Arabia

Artificial intelligence and deep learning for medical image generation, analysis, and segmentation.

1. F. Asadi, T. Angsuwatanakul, and J. A. O'Reilly, "Evaluating synthetic neuroimaging data augmentation for automatic brain tumour segmentation with a deep fully-convolutional network," IBRO Neuroscience Reports, vol. 16, pp. 57–66, 2024.
2. F. Asadi, K. Thangthong, and S. Tungjitkusolmun, "Common Spatial Pattern Variants for Feature Extraction in Multi-Class Motor Imagery BCI," in Proc. BMEiCON, 2025, pp. 1–5.
3. F. Asadi and J. A. O'Reilly, "Artificial computed tomography images with progressively growing generative adversarial network," in Proc. BMEiCON, 2021, pp. 1–5.
4. F. Asadi, "Synthetic data for deep learning medical applications: generation, evaluation, and utilization," Ph.D. dissertation, Rangsit University, Thailand, 2024.
5. J. A. O'Reilly and F. Asadi, "Pre-trained vs. random weights for calculating Fréchet inception distance in medical imaging," in Proc. BMEiCON, 2021, pp. 1–4.