Ahmed Solyman

Lecturer

Glasgow Caledonian University

United Kingdom

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Ahmed Solyman is a Lecturer at Glasgow Caledonian University in the United Kingdom. His research areas include machine learning applications in material design, driving fatigue recognition through EEG signals, and deep learning methodologies for medical imaging. He has also explored topics related to wireless communication networks, including 5G systems and intelligent reflecting surfaces in UAV communications. His recent publications highlight the intersection of artificial intelligence, electrical engineering, and biomedical applications.

Articles (12)

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2025

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2024

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2023

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2023

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2022

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2022

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2022

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2022

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2022

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2022

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2022

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2022

Collaborators (2)

Mahdi Abbasi

Associate Professor

Umeå Universitet

SWEDEN

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Ioannis J Vourganas

Abertay University

UNITED KINGDOM

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Ahmed Solyman

Research Interests

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Articles (12)

Machine learning alloying design of biodegradable zinc alloy for bone implants using XGBoost and Bayesian optimization

A Hybrid Deep Neural Network Approach to Recognize Driving Fatigue Based on EEG Signals

Synthetic Generation of Multidimensional Data to Improve Classification Model Validity

Investigating and calculating the temperature of hot-spot factor for transformers

5G System Overview for Ongoing Smart Applications: Structure, Requirements, and Specifications

Impacts of integration of wind farms on voltage stability margin

Diagnosis of Oral Squamous Cell Carcinoma Using Deep Neural Networks and Binary Particle Swarm Optimization on Histopathological Images: An AIoMT Approach

Simple Mathematical and Simulink Model of Stepper Motor

Evolution of wireless communication networks: from 1G to 6G and future perspective

Intelligent Reflecting Surfaces Assisted UAV Communications for Massive Networks: Current Trends, Challenges, and Research Directions

Prediction of Wear Rates of UHMWPE Bearing in Hip Joint Prosthesis with Support Vector Model and Grey Wolf Optimization

Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model

Collaborators (2)

Mahdi Abbasi

Ioannis J Vourganas

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