Dr. Qamar Natsheh

Dr. Qamar Natsheh

School of Computer Science
Assistant Professor (Flying Faculty)

Contact details

Address
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Qamar is an Assistant Professor in Computer Science at the University of Birmingham, serving as Flying Faculty between the Edgbaston and Dubai campuses. She is also a member of the Perception, Language, Action (PLA) group. Her research interests span medical imaging, image processing technologies, computer vision, and data science.

Qualifications

  • Ph.D. in Medical Image Security, Loughborough University
  • M.Sc. in Visual Systems and Technology, Loughborough University
  • B.Sc. in Computer Science, The University of Jordan

Fellowships:

  • FHEA, Fellow of the Higher Education Academy, UK, 2023

Teaching

  • Computer Systems and Professional Practice
  • Artificial Intelligence and Machine Learning
  • AI Programming
  • Algorithms for Data Science
  • Programming for Data Science
  • Data Science Group Project

Research

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.