Dr. Alyaa Amer

Assistant Professor - College of Computer Information Technology

Dr. Alyaa Amer is an Assistant Professor at the College of Computing and Information Technology, Arab Academy for Science and Technology. She has over 14 years of full-time teaching and research experience in computer science and engineering. She obtained her PhD from the Department of Computer Science, University of Lincoln, U.K. Her research delved into the development of innovative deep-learning models for medical image segmentation, classification, and detection, in attempt to help physicians in their diagnosis and decision-making. Her research has garnered significant recognition, leading to publications in reputable journals that highlight the impact and relevance of my studies. Through her dedicated teaching experience at the college level, she has developed an extensive comprehension of computer science principles and a good talent for presenting complicated concepts in an interactive and comprehensible way. In addition to teaching, she has held several administrative positions which include head of the control committee, head of the student advising committee, and member of the quality control committee. Beyond her professional pursuits, Dr. Alyaa is dedicated to encouraging innovative thinking among her students.

Cover Date	Title	Citations
Jan/01/2023	MCA-Unet: A multiscale context aggregation U-Net for the segmentation of COVID-19 lesions from CT images	0
Apr/01/2022	MDA-Unet: A Multi-Scale Dilated Attention U-Net For Medical Image Segmentation	31
Jan/01/2021	ResDUnet: A Deep Learning-Based Left Ventricle Segmentation Method for Echocardiography	28

Cover Date	Title	Citations
Jan/01/2013	Chord-Enabled Key Storage and Lookup Scheme for Mobile Agent-Based Hierarchical WSN	2
Jan/01/2025	Generalized Polyp Detection from Colonoscopy Frames Using Proposed EDF-YOLO8 Network	0

Cover Date	Title	Citations
Jul/01/2020	ResDUnet: Residual Dilated UNet for Left Ventricle Segmentation from Echocardiographic Images	22
Jan/01/2021	Residual Dilated U-net for the Segmentation of COVID-19 Infection from CT Images	9