Researcher at IUBAT - International University of Business Agriculture and Technology
I am a researcher in the field of Electrical and Electronic Engineering specializing in the development of optimized deep learning architectures. My work focuses on advancing model interpretability and performance through hybrid frameworks, including the integration of Convolutional Neural Networks (CNNs) and Vision Transformers (ViT). Having published academic papers on CNN-based classification, I have extensive experience implementing complex models for diverse applications ranging from agricultural imagery to real-time fault detection in lithium-ion batteries. I am particularly interested in leveraging Bayesian optimization and Explainable AI (XAI) techniques, such as Grad-CAM and SHAP, to create more transparent and efficient intelligent systems. Currently, I am dedicated to bridging the gap between theoretical deep learning research and practical, high-performance deployments in cloud-based environments.