Khaled obtained his BA-ICT from Swinburne Sarawak in 2019 and his Master of Science (Computer Science) from the same institution in 2022. His Master’s thesis focused on age detection using deep learning, while also developing a system to detect GAN-generated images. Khaled is currently in the final stages of his PhD, which centers on polyp detection using deep learning. In his PhD research, he explored a novel alternative to channel and spatial attention mechanisms, aiming to improve detection accuracy and efficiency in medical imaging tasks. Khaled’s primary research interests lie in deep learning and computer vision, with a particular focus on optimizing model architectures for specialized applications such as medical imaging and image manipulation detection. His work mainly explores the theoretical and low-level aspects of deep learning, particularly self-attention mechanisms and tokenization strategies, as well as the development of more efficient and interpretable models.
Potential research higher degree candidates are welcome to enquire about postgraduate opportunities in the areas listed above. Please e-mail kelkaeazle@swinburne.edu.my for more information.
