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Hina Tabassum

Hina Tabassum (Senior Member, IEEE)  received her bachelor’s degree in Electronics Engineering from NED University of Technology (NEDUET). She secured first position among all engineering universities of Karachi, Pakistan. For her achievement,  she received Gold medals from NEDUET and from SIEMENS. She then joined R&D at Pakistan …

Differentiable Projections for Guaranteed Convex/Non-convex Constraints Satisfaction in Deep Learning Empowered Wireless Radio Resource Management

By. Hina Tabassum
The next generation of wireless networks is anticipated to be more complex and heterogeneous due to higher transmission frequencies, massive antenna arrays, ultra-dense deployments, mobility of transceivers, and static/dynamic link blockages. These features lead to faster variations in the propagation channel. Subsequently, the …

Dr. Ajmery Sultana

Dr. Ajmery Sultana
Vice-Chair , Communication Chapter and Vehicular Technology Chapter 
Dr. Ajmery received her Ph.D degree from the Department of Electrical and Computer Engineering, Toronto Metropolitan University (formerly Ryerson University), Toronto, ON, Canada, in 2018. She served as a postdoctoral fellow at the Department of Computer …

Dr. Ammar Al-Qaraghuli

Dr. Ammar Al-Qaraghuli is a dynamic educator and innovator, recognized for his significant contributions to both academia and industry. With over 15 years of experience in teaching, research, and project management, Dr. Al-Qaraghuli has dedicated his career to developing talent and driving positive change. 
Having earned …

Mouhamed Abdulla

Dr. Mouhamed Abdulla

Mouhamed Abdulla (S’02-GSM’09-M’12) is a Professor of Electrical Engineering with the School of Mechanical and Electrical Engineering of the Faculty of Applied Science and Technology at Sheridan Institute of Technology and Advanced Learning in Ontario, Canada. At Sheridan, he developed and taught various …

A Study Comparing YOLOv8 and Detector2 for Object Segmentation Defect Identification

Dr. Ameera Al-Karkhi
Sheridan College/ Faculty of Applied Science and Technology
Within the field of computer vision and image processing, object segmentation defect detection is crucial for a number of industries, such as manufacturing, healthcare, and autonomous systems. Accurately quickly detecting defects is critical for ensuring the …