About me

I am a dedicated researcher in machine learning and computer vision, specialising in hierarchical classification and deep learning architectures. Currently, I am completing my PhD in Computer Vision, focusing on Neural Architectures for Hierarchical Classification by Agreement. My work involves designing and implementing advanced neural network models to enhance classification accuracy and interpretability across diverse domains, including facial recognition, medical imaging, and underwater sensing.

My research interests include capsule networks, hierarchical multi-label classification (HMC), and agreement-based learning mechanisms. I have developed novel deep learning models, which leverage hierarchical taxonomy structures for improved decision-making in complex classification tasks. I am also actively engaged in optimising feature extraction, routing mechanisms, and saliency-based visualisation techniques in deep networks.

Beyond my research, I am passionate about applying machine learning solutions to real-world problems, bridging the gap between theory and practice. I am keen on contributing to academia and industry through publications, collaborations, and innovative AI-driven applications.

Feel free to connect with me to discuss research opportunities, collaborations, or AI-driven solutions.