Research Excellence Award
Omar El Ogri — Sidi Mohamed Ben Abdellah University, Morocco
Omar El Ogri is a researcher affiliated with Sidi Mohamed Ben Abdellah University, Morocco, whose documented work spans artificial intelligence, deep learning, image analysis, optimization, and data-driven prediction. His recent publications address solar-panel fault classification, educational prediction, and computer-assisted cancer diagnosis using computational methods and feature representations in applied research. [1] [2] [3]
Abstract
Omar El Ogri is a researcher at Sidi Mohamed Ben Abdellah University in Morocco whose work focuses on artificial intelligence and its applications in image analysis, machine learning, optimization, and predictive modeling. His documented publications address automated solar-panel fault classification, academic achievement and school-dropout prediction, and computer-assisted cancer diagnosis. The studies combine specialized mathematical representations, optimization algorithms, and deep-learning architectures to develop computational approaches for domain-specific problems. His recent research illustrates interdisciplinary applications spanning renewable-energy inspection, education, and biomedical image analysis. The supplied academic record reports 42 documents, 905 citations, and an h-index of 16 within an evolving research portfolio.
Keywords
- Artificial Intelligence
- Deep Learning
- Computer Vision
- Image Analysis
- Machine Learning
- Optimization Algorithms
- Biomedical Image Analysis
- Predictive Analytics
Introduction
Omar El Ogri is a researcher affiliated with Sidi Mohamed Ben Abdellah University, Morocco, whose documented work spans artificial intelligence, deep learning, image analysis, optimization, and data-driven prediction. His recent publications address solar-panel fault classification, educational prediction, and computer-assisted cancer diagnosis using computational methods and feature representations in applied research. [1] [2] [3]
Research Profile
El Ogri’s research profile reflects an interdisciplinary application of artificial intelligence to image-based recognition, predictive modeling, and optimization. His reported record includes 42 documents, 905 citations, and an h-index of 16, with Artificial Intelligence identified as his subject area. These indicators provide context for assessing his research activity and visibility. [4]
Research Contributions
His documented contributions include combining Krawtchouk moments with optimized deep transfer learning for solar-panel fault classification, developing Artificial Bee Colony-based models for educational prediction, and proposing Rademacher-Fourier moment representations with deep learning for cancer-image diagnosis. Together, these studies demonstrate methodological work across computer vision, optimization, classification, and predictive analytics applications. [1] [2] [3]
Publications
Selected publications illustrate the breadth of El Ogri’s research collaborations. Recent work includes a solar-panel fault classification study using Krawtchouk moments and EfficientNetB4, an educational prediction study using Artificial Bee Colony optimization, and a medical diagnosis study combining Rademacher-Fourier moments with deep learning for biomedical image analysis and recognition systems. [1] [2] [3]
Research Impact
The cited studies indicate research impact through application-oriented methods addressing renewable-energy inspection, educational analytics, and biomedical image analysis. Reported experiments include high classification and prediction performance within their respective datasets, while the publications contribute specialized feature-extraction, optimization, and machine-learning approaches. These findings support continued investigation across applied artificial intelligence domains. [1] [2] [3]
Award Suitability
Based on the supplied academic record and documented publications, the Research Excellence Award recognizes a profile centered on artificial intelligence research and applied computational methodologies. The combination of activity, citation indicators, interdisciplinary applications, and methodological studies provides evidence for considering the researcher’s contributions within the stated Technology Scientists Awards context. [1] [2] [3]
Conclusion
Omar El Ogri’s documented research demonstrates sustained engagement with artificial intelligence, machine learning, image analysis, and optimization. His recent publications address distinct application areas while introducing specialized computational techniques. The available record presents a coherent research profile combining methodological development with practical problems in energy, education, and biomedical image analysis. [1] [2] [3]
External Links
References
- Naouadir, I., El Ogri, O., El-Mekkaoui, J., Benslimane, M., & Hjouji, A. (2026). A deep transfer learning and optimized Krawtchouk moment-based system for fault classification in solar panels. Computers & Electrical Engineering, 138, 111324.
https://www.sciencedirect.com/science/article/abs/pii/S0045790626003940
- El Yousfi Alaoui, H., Bousraraf, Z., Hjouji, A., El Ogri, O., & El-Mekkaoui, J. (2026). New regression model for academic achievement and new classification method for school dropout based on Artificial Bee Colony Algorithm. Statistics, Optimization & Information Computing, 15(5), 3401–3415.
https://iapress.org/index.php/soic/article/view/2420
- El Ogri, O., El-Mekkaoui, J., & Hjouji, A. (2026). A computer-assisted medical diagnosis system for cancer diseases based on quaternion orthogonal Rademacher-Fourier moments and deep learning. Biomedical Signal Processing and Control, 112, 108744.
https://www.sciencedirect.com/science/article/abs/pii/S1746809425012558
- Elsevier. (n.d.). Scopus author details: Omar El Ogri, Author ID 59208342000. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=59208342000
