Enoch Kwateh Dongbo

Master's Student (Computer Science and Technology)

Enoch Kwateh Dongbo is a researcher specializing in computer vision, deep learning, and adversarial machine learning. He is currently pursuing a Master of Engineering in Computer Science and Technology at the University of Jinan, China, where his research focuses on developing robust and interpretable AI models for medical imaging applications. His work explores the intersection of model robustness, attention mechanisms, and pruning strategies, aiming to enhance the resilience of neural networks against adversarial attacks while preserving diagnostic accuracy. Recent projects include MedDef, an efficient self-attention model designed to defend medical imaging systems from adversarial perturbations, and a hybrid deep learning framework combining ResNeXt and Twin Fuzzy Extreme Learning Machines (TFELM) for high-accuracy image classification. Enoch's long-term goal is to advance trustworthy and secure artificial intelligence, ensuring that deep learning systems used in healthcare are both reliable and explainable.