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Prof. Walid Al-Atabany

Associate Dean for UG Programs

Faculty Building

UB1

Office Number

210

Biography

Professor Walid Al-Atabany's academic journey began with the completion of his B.Sc. and M.Sc. degrees at Cairo University's Biomedical Engineering Department in 1999 and 2004, respectively. In 2010, he achieved his Ph.D. in biomedical engineering from Imperial College London. In 2011, Professor Al-Atabany embarked on a two-year research associate position at Newcastle University, further enriching his expertise. Currently, He is a full professor at Nile University's Information Technology and Computer Science (ITCS) School. Within ITCS, he also serves as the Vice Dean of Student Affairs and the Director of the Quality Unit. Professor Al-Atabany's research interests is highly interdisciplinary, with a primary focus on developing assistive technologies for the visually impaired and advancing prosthetic vision. His research portfolio has also expanded to encompass critical issues in healthcare technology enhancement. Notably, his scholarly contributions have made a significant impact, boasting over 70 published articles in esteemed journals and conferences, which have garnered more than 3000 citations.

Professor Al-Atabany's dedication and contributions to the field have earned him numerous awards and grants, including the prestigious Scientific Excellence Award from Nile and Helwan Universities in 2023 and 2021, respectively. He has also been a recipient of two Newton-Mosharafa grants from the British Council in 2015 and 2016, as well as the travel grant from the ARVO Foundation for Eye Research in 2010, Maryland.

Achievements
  1. Prof. Walid Al-Atabany has receive the Prof. Hazem Ezzat award for the Outstanding Faculty Researcher from Nile University in 2023.
  2. He also earned the Scientific Excellence Award for having excellent record of international publications, 2021.
  3. He received a 2-year Newton institutional link grant from the British Council to conduct joint research with the School of Electrical and Electronic Engineering at Newcastle University in 2016.
  4. He was awarded a 6-month prestigious Newton travel grant from the British Council to conduct joint research at Newcastle University in 2015.
  5. He won the 2nd prize award from the 2nd Symposium of the Neuroscience Technology Network (NTN2009).
Recent Publications

Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems

Recently, the numerical optimization field has attracted the research community to propose and develop various metaheuristic optimization algorithms. This paper presents a new metaheuristic optimization algorithm called Honey Badger Algorithm (HBA). The proposed algorithm is inspired from the intelligent foraging behavior of honey badger, to mathematically develop an efficient search strategy for

Circuit Theory and Applications

Classification of Thyroid Carcinoma in Whole Slide Images Using Cascaded CNN

The objective of this research is to build a 'Whole Slide Images' classification system using Convolutional Neural Network (CNN). This system is capable of classifying Thyroid tumors into three types: Follicular adenoma, follicular carcinoma, and papillary carcinoma. Furthermore, the cascaded CNN technique is additionally employed to classify the classified follicular carcinoma into four

Artificial Intelligence
Healthcare

Corneal Biomechanics Assessment Using High Frequency Ultrasound B-Mode Imaging

Assessment of corneal biomechanics for pre- and post-refractive surgery is of great clinical importance. Corneal biomechanics affect vision quality of human eye. Many factors affect corneal biomechanics such as, age, corneal diseases and corneal refractive surgery. There is a need for non-invasive in-vivo measurement of corneal biomechanics due to corneal shape preserving as opposed to ex-vivo

Artificial Intelligence

An E-health System for Encrypting Biosignals Using Triple-DES and Hash Function

This Electronic Health (E-Health) is a broad expression that enables the communication between healthcare professionals in handling patient information through the cloud. Exchanging medical data over the public cloud requires securing transferring for the data that's direct many researchers in proposing different secure schemes to enable users to handle data safely without hacking or alternating

Artificial Intelligence

Robust Background Template for Saliency Detection

In this paper, we propose an effective saliency detection method based on dense and sparse representation in-terms of an optimized background template. Firstly, the input image is divided into compact and uniform super-pixels. Then, the optimized background template is produced by introducing boundary conductivity measurement to improve the dense and sparse representation of the image's super

Artificial Intelligence

Instance Segmentation of 2D Label-Free Microscopic Images using Deep Learning

The precise detection and segmentation of cells in microscopic image sequences is an essential task in biomedical research, such as drug discovery and studying the development of tissues, organs, or entire organisms. However, the detection and segmentation of cells in phase contrast images with a halo and shade-off effects is still challenging. Lately, Mask Regional Convolutional Neural Network

Artificial Intelligence
Healthcare
Innovation, Entrepreneurship and Competitiveness

Studying Genes Related to the Survival Rate of Pediatric Septic Shock

Pediatric septic shock is generally considered as a devastating clinical syndrome that can lead to tissue damage and organ failure due to the over exaggerated immune response to an infection. Therefore, in this paper, we attempted to early identify the clinical course of such disease with the aid of peripheral blood T-cells of 181 pediatric patients who admitted to Intensive Care Unit (ICU)

Artificial Intelligence
Healthcare
Innovation, Entrepreneurship and Competitiveness

INVESTIGATION OF DIFFERENTIALLY EXPRESSED GENE RELATED TO HUNTINGTON'S DISEASE USING GENETIC ALGORITHM

neurodegenerative diseases have complex pathological mechanisms. Detecting disease-associated genes with typical differentially expressed gene selection approaches are ineffective. Recent studies have shown that wrappers Evolutionary optimization methods perform well in feature selection for high dimensional data, but they are computationally costly. This paper proposes a simple method based on a

Artificial Intelligence
Healthcare
Software and Communications
Research Tracks
  • Biomedical Informatics
  • Medical Imaging
  • Image Processing MIIP
Projects
IMG
Research Project

Portable Ophthalmoscope for Telemedicine Retinopathy of Prematurity (ROP) Screening in Egypt

Few diseases affect human life and personal destinies more than the loss of the ability to see. In adults, visual impairment is associated with a loss of personal independence inducing large personal and societal costs. According to the World Health Organization, 39 million people are legally blind. In Egypt, there are almost 1 million individuals (~1% of the population) with sight loss. The