Dr. Ramsha Ahmed earned her PhD in Information and Communication Engineering from the University of Science and Technology Beijing (USTB) in China, where she graduated with distinction in 2022. Before this, she completed her Bachelor's in Electrical (Telecommunication) Engineering in 2013 and her Master's in Information Security in 2017, both from the National University of Sciences and Technology (NUST), Pakistan.
Beyond her academic achievements, Dr. Ahmed has substantial industry experience. She has served with prominent companies in Pakistan, including the Pakistan Telecommunication Company Ltd (PTCL) and the National Telecommunication Corporation (NTC), in various capacities related to data communication, planning, and development. Additionally, she has benefited from specialized training sessions in information security at both Sandia National Laboratories (SNL) and George Washington University (GWU) in the USA.
Currently, Dr. Ahmed is advancing her research at Khalifa University (KU) in the UAE as a postdoctoral fellow in the domain of medical imaging and computer vision. As a member of the Healthcare Engineering Innovation Center (HEIC), she is focused on developing advanced automated methods harnessing deep learning to meticulously segment stroke lesions in clinical MRI scans, under the esteemed guidance of Prof. Mohamed Seghier and Prof. Naoufel Werghi.
Segmentation of Stroke Lesions in Clinical MRI Scans
Automated delineation of stroke lesions from monospectral MRI scans is very helpful for diverse research and clinical applications, including lesion-symptom mapping to explain deficits and predict recovery, tracking changes over time, and helping with treatment plans. In this research, we aim to develop advanced automated methods based on deep learning to isolate brain abnormalities in clinical MRI scans.
