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How has Omar Shalash's publication output changed over time?
ScholarIQpublication output · 2023–2025
Output grew0% over the shown period — from 3 works in 2023 to 3 in 2025.
3
5
3
202320242025
What are the most-cited papers on Omar Shalash?
ScholarIQmost cited works
A Data-Driven Digital Twin of Electric Vehicle Li-Ion Battery State-of-Charge Estimation Enabled by Driving Behavior Application Programming Interfaces
Reda Issa, Mohamed M. Badr, Omar Shalash, Ali A. Othman, Eman Hamdan, Mostafa S. Hamad, Ayman S. Abdel‐Khalik, Shehab Ahmed, Sherif M. Imam
S2737090608. 202342 CitationsOPEN ACCESS
Optimized Decentralized Swarm Communication Algorithms for Efficient Task Allocation and Power Consumption in Swarm Robotics
Mohamed Yasser, Omar Shalash, Ossama Ismail
S4210232487. 202421 CitationsOPEN ACCESS
Computer-assisted robotic system for autonomous unicompartmental knee arthroplasty
Omar Shalash, Philip Rowe
S2764413287. 202312 CitationsOPEN ACCESS
Empowering the Grid: A Comprehensive Review of Artificial Intelligence Techniques in Smart Grids
Marwa Elkholy, Omar Shalash, Mostafa S. Hamad, Mohamed S. Saraya
202412 Citations
Enhancing hydroponic farming with Machine Learning: Growth prediction and anomaly detection
Ahmed Métwalli, Omar Shalash, Alia Elhefny, Nour Rezk, Fares El Gohary, Omar El Hennawy, Fouad Akrab, Adam Shawky, Ziad Mohamed, Nayira Hassan, Mostaafa Hassanen
Engineering Applications of Artificial Intelligence. 202512 Citations
Related on ScholarIQ
Ajman University
Institution
A Data-Driven Digital Twin of Electric Vehicle Li-Ion Battery State-of-Charge Estimation Enabled by Driving Behavior Application Programming Interfaces
Paper
Optimized Decentralized Swarm Communication Algorithms for Efficient Task Allocation and Power Consumption in Swarm Robotics
Paper
Computer-assisted robotic system for autonomous unicompartmental knee arthroplasty
Paper
Empowering the Grid: A Comprehensive Review of Artificial Intelligence Techniques in Smart Grids
Paper
Enhancing hydroponic farming with Machine Learning: Growth prediction and anomaly detection
Paper