Qamar’s research spans medical imaging, image processing technologies, computer vision, and data science, with a particular focus on medical image security in healthcare systems. In addition to her research in medical imaging, she worked on a short project with Apical (now part of ARM) on enhancing colour constancy in camera pipelines, contributing to advancements in image processing.
She is deeply interested in neuroscience research that focuses on improving educational approaches for neurodivergent individuals. Her research aims to bridge the gap between neuroscience and pedagogical strategies by leveraging AI and neuroimaging technologies to enhance learning outcomes for individuals with diverse cognitive needs. This research has the potential to transform educational practices, offering more personalised and inclusive support for neurodivergent individuals.
Furthermore, she is passionate about data science research, particularly in sports science and healthcare systems. She supervises students on projects that apply data science techniques to address challenges and generate insights in this interdisciplinary field.