Yumna Zahid

Yumna Zahid is a researcher in the Department of Computer Science at Aberystwyth University. Her work focuses on advancing machine learning and computer vision techniques, particularly in anomaly detection, few-shot learning, and surveillance systems. She has contributed to methods addressing challenges in long-tailed visual recognition and scene adaptation through deep learning frameworks.

Her research aligns with UN Sustainable Development Goals, enhancing technological solutions for societal challenges. Key collaborations include studies on adversarial diffusion for video anomaly detection and ensemble learning approaches for surveillance applications.

Publications span topics like ensemble frameworks (IBaggedFCNet), cache optimization in multicore systems, and variational methods in few-shot learning. Zahid's work emphasizes practical applications, such as improving predictive accuracy in security systems and optimizing computational resources.