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.
Journal of Industrial and Production Engineering
This review examines explainable AI methods for industrial fault detection and diagnosis. It proposes a taxonomy covering model-agnostic methods, model-specific approaches, and hybrid rule-based schemes, and discusses their use in revealing fault-related decision logic. The review also highlights key implementation limits, including computational cost, real-time performance, and scalability.
Energy and Buildings
This study proposes a Double Stacking Ensemble Learning framework for short-term solar irradiance prediction in regions with limited ground-based observations.
Sustainable Production and Consumption
A fire-extinguisher manufacturing case shows a 50% reduction in sustainability costs.
Energy
Machine learning analysis of butanol combustion using flame images.
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
This course provides students with hands-on experience using modern tools and platforms for big data processing and analysis. Students learn to work with large-scale datasets using distributed computing frameworks and cloud-based analytics solutions.
Key Topics:
- Big Data Platforms and Architecture
- Distributed Computing Frameworks
- Data Processing Pipelines
- Cloud-Based Analytics
- Real-Time Data Processing
This course covers the statistical principles and methodologies for designing and analyzing experiments in engineering and scientific research. Students learn to plan, conduct, and interpret experimental studies to optimize processes and products.
Key Topics:
- Factorial Designs
- Response Surface Methodology
- Taguchi Methods
- Fractional Factorial Designs
- Analysis of Variance (ANOVA)
Get in Touch
Interested in collaborating or have questions about my research? Feel free to reach out.
American University of Sharjah
Sharjah, UAE
