Ahmed Maged
Assistant Professor of Industrial Engineering
Dedicated to innovative research and practical applications in advanced industrial processes. Focused on Intelligent Manufacturing, Quality Engineering, Anomaly Detection and Deep Learning.
About Me
I am Ahmed Maged, an Assistant Professor of Industrial Engineering at the American University of Sharjah. My research focuses on Intelligent Manufacturing, Quality Engineering, Anomaly Detection and Deep Learning.
Education
Ph.D. in Systems Engineering
City University of Hong Kong, 2023
M.S. in Industrial Engineering
Benha University, 2017
B.S. in Mechanical Engineering
Benha University, 2013
Awards & Honors
Outstanding Academic Performance
City University of Hong Kong,2022
Research Tuition Scholarship
City University of Hong Kong,2021
Research Tuition Scholarship
City University of Hong Kong,2020
Best Paper Award
International Conference on Indsutrial Engineering and Operations Management, 2019
Excellence in Research
Benha University, 2018,2024
Research
My research focuses on developing advanced methodologies for industrial systems optimization, quality improvement, and intelligent manufacturing.
"Without data, you're just another person with an opinion."
Developing statistical and computational methods for quality control, process optimization, and robust design in manufacturing systems.
Creating advanced algorithms for early detection and accurate diagnosis of faults in complex industrial systems and manufacturing processes.
Applying deep learning and AI techniques for anomaly detection, predictive maintenance, and intelligent decision-making in manufacturing environments.
Publications
Selected peer-reviewed publications from my research.
Biomedical Signal Processing and Control, 2024
This study presents an explainable framework for automatic brain abnormality detection in MRI images. The methodology includes a robust preprocessing pipeline and employs EfficientViT for classification, achieving up to 99.24% accuracy across various datasets. The model outperformed traditional deep learning techniques and provides explainable results to aid neurologists in diagnosis.
Fuel, 2024
This study uses deep learning to predict combustion pressure from flame images captured from a single-cylinder optical GDI engine. Five models were tested, with EfficientNetB4 achieving the best performance (R² of 0.94). Saliency analysis revealed the model detects subtle flame characteristics invisible to the human eye, advancing machine learning approaches for engine design and optimization.
Sustainable Production and Consumption, 2025
This study introduces a sustainable approach for monitoring manufacturing processes by optimizing the np chart to account for environmental and economic impacts. The optimal chart enhances detection of increasing shifts in nonconforming items, reducing emissions and costs. An application on fire extinguisher manufacturing demonstrated a 50% reduction in sustainability costs compared to conventional methods.
Courses
Courses I teach at the American University of Sharjah.
This course introduces students to the principles and techniques of quality engineering in manufacturing and service systems. It covers statistical process control, design of experiments, and quality improvement methodologies.
Key Topics:
- Statistical Process Control (SPC)
- Design of Experiments (DOE)
- Six Sigma Methodology
- Acceptance sampling Plans
- Total Quality Management
The Manufacturing Processes course for Industrial Engineering focuses on understanding how products are made through casting, forming, machining, joining, and additive methods. It covers material properties, process selection, tooling, quality control, and basic lean principles to improve production efficiency. Students learn both theory and practical aspects, including process planning, cost considerations, and the use of measurement tools.
Key Topics:
- Introduction to manufacturing and process planning with focus on cost, safety, and environmental impact
- Machining, metal cutting economics, and metal casting processes and equipment
- Plastic shaping, composite processing, powder metallurgy, ceramics, and metal forming (rolling, forging, extrusion)
- Additive manufacturing, nano fabrication, and joining processes
Get in Touch
Interested in collaborating or have questions about my research? Feel free to reach out.
American University of Sharjah
Sharjah, UAE
