Prof. Dr. Badr Abou El Majd | Applied Mathematics | Mathematical Engineering Excellence Award

Full Professor at Mohammed V University, Morocco

Dr. Badr Abou El Majd is a distinguished Professor of Applied Mathematics at Mohammed V University, Rabat, with extensive expertise in multidisciplinary optimization, shape design, AI-driven modeling, and computational engineering. Holding a Ph.D. from INRIA Sophia Antipolis and a Master’s from Pierre and Marie Curie University, his research spans aerospace, transportation, smart systems, and biomedical applications. He has authored over 80 peer-reviewed publications, edited scientific volumes, and holds several patents. As a leader in numerous international research projects and conferences, including EU Erasmus+ and IEEE events, Dr. Abou El Majd has demonstrated remarkable scientific leadership. His contributions to innovation, education, and cross-border collaboration are further recognized through awards like the Distinguished Scholar Award (2023–24), making him a pivotal figure in advancing research that bridges theory, technology, and real-world societal needs

Professional Profile

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Education

Dr. Badr Abou El Majd holds a Ph.D. in Applied Mathematics from INRIA Sophia Antipolis – Méditerranée, France (2007), where he specialized in hierarchical algorithms and game strategies for multidisciplinary optimization, with applications in aerospace design. His doctoral work was conducted in collaboration with Dassault Aviation and Piaggio Aero, demonstrating strong industrial-academic integration. He also earned a Master’s degree in Numerical Analysis from Pierre and Marie Curie University (UPMC – Paris 6), one of Europe’s leading institutions in mathematical sciences. His early academic path was marked by a strong foundation in computational mathematics, optimization, and numerical modeling. These formative years provided the analytical and algorithmic rigor that continues to define his research contributions across disciplines such as aerospace engineering, smart systems, and data-driven decision-making.

Experience

With over two decades of academic and research experience, Dr. Abou El Majd has held prominent roles in Morocco and internationally. He is currently a Full Professor at Mohammed V University, Rabat. Previously, he served as an Associate Professor at both the International University of Rabat and Hassan II University in Casablanca. His international exposure includes visiting and research positions at INRIA Lille, University of Lille, and Polytechnique Montréal. He also worked as a scientist researcher at École Centrale Paris and completed post-doctoral research at CNRS/ENSMA. He has led and coordinated large-scale research and tech-transfer projects involving multiple institutions, government bodies, and industry leaders. This broad experience has enabled him to seamlessly bridge academic theory, industrial application, and international collaboration in fields ranging from aerospace to smart agriculture.

Research Interests

Dr. Abou El Majd’s research is deeply rooted in applied mathematics and multidisciplinary optimization, with expansive interests spanning aerodynamic shape design, robust optimization, artificial intelligence, model reduction, decision-making systems, and digital twin frameworks. He actively explores how machine learning, game theory, and numerical methods can be applied to real-world engineering and societal problems. His work spans diverse domains including aerospace design, RFID networks, cognitive radio, smart agriculture, biomedical imaging, and manufacturing optimization. Through his research, he aims to solve high-dimensional, complex optimization problems while ensuring scalability and industrial relevance. He has recently focused on surrogate modeling, AutoML, and intelligent systems for healthcare diagnostics and infrastructure planning, reflecting a strong commitment to leveraging computational science for impactful, cross-disciplinary solutions.

Award and Honor

Dr. Abou El Majd’s contributions to science and innovation have earned him several prestigious honors. Most notably, he received the Distinguished Scholar Award (2023–24) from the Arab Fund for Economic and Social Development, in collaboration with the University of Lille—an acknowledgment of his outstanding research achievements and academic leadership. Earlier, his doctoral studies were supported by a competitive scholarship from Dassault Aviation and Piaggio Aero, underscoring the industrial relevance of his research. He has also secured major research grants from Erasmus+, CNRST Morocco, TUBITAK Turkey, and the OCP Foundation, amounting to several million dirhams. These accolades reflect not only the scientific merit of his work but also its strategic importance in fields such as transportation, defense, AI, and healthcare systems optimization.

Research Skills

Dr. Abou El Majd possesses a robust and diverse skill set spanning numerical optimization, algorithm design, scientific programming, and AI integration. He is proficient in developing multilevel optimization frameworks, parameterization techniques, and model reduction strategies. His capabilities extend to software architecture, cloud platform development, and AI-enhanced decision systems. He has implemented and applied methods like genetic algorithms, particle swarm optimization, and POD-based reduced-order modeling. His technical expertise is complemented by certifications in Business Intelligence (IBM), Big Data Analytics (Griffith University), and Artificial Intelligence (Accenture). His ability to lead multidisciplinary teams and integrate computational techniques with industrial challenges makes him an effective innovator and collaborator. He also brings strong experience in simulation, CFD, robust design, and real-time optimization across diverse technological sectors.

Publication Top Notes

• Title: Calibration of POD Reduced‐Order Models Using Tikhonov Regularization
  Authors: L. Cordier, B. Abou El Majd, J. Favier
  Year: 2010
  Citations: 183

• Title: Nested and Self-Adaptive Bézier Parameterizations for Shape Optimization
  Authors: J.A. Désidéri, B. Abou El Majd, A. Janka
  Year: 2007
  Citations: 90

• Title: A Particle Swarm Optimization Based Algorithm for Primary User Emulation Attack Detection
  Authors: W.F. Fihri, Y. Arjoune, H. El Ghazi, N. Kaabouch, B. Abou El Majd
  Year: 2018
  Citations: 34

• Title: Multilevel Strategies for Parametric Shape Optimization in Aerodynamics
  Authors: B. Abou El Majd, J.A. Désidéri, R. Duvigneau
  Year: 2008
  Citations: 28

• Title: Deep Learning-Based Intrusion Detection System for Advanced Metering Infrastructure
  Authors: Z. El Mrabet, M. Ezzari, H. Elghazi, B.A. El Majd
  Year: 2019
  Citations: 24

• Title: Primary User Emulation Attacks: A Detection Technique Based on Kalman Filter
  Authors: Z.E. Mrabet, Y. Arjoune, H.E. Ghazi, B.A.A. Majd, N. Kaabouch
  Year: 2018
  Citations: 23

• Title: Embedding Lattice Structures into Ship Hulls for Structural Optimization and Additive Manufacturing
  Authors: A. Armanfar, A.A. Tasmektepligil, R.T. Kilic, S. Demir, S. Cam, Y. Karafi, B.A. El Majd, et al.
  Year: 2024
  Citations: 20

• Title: Bayesian Decision Model with Trilateration for Primary User Emulation Attack Localization in Cognitive Radio Networks
  Authors: W.F. Fihri, H. El Ghazi, N. Kaabouch, B.A. El Majd
  Year: 2017
  Citations: 20

• Title: Homogenization of Periodic Structured Materials with Chiral Properties
  Authors: O. Ouchetto, B.A. El Majd, H. Ouchetto, B. Essakhi, S. Zouhdi
  Year: 2016
  Citations: 20

• Title: Aerodynamic Shape Optimization Using a Full and Adaptive Multilevel Algorithm
  Authors: B. Abou El Majd, R. Duvigneau, J.A. Désidéri
  Year: 2006
  Citations: 20

• Title: LSTM-Based Neural Network Architecture for Predicting the Nonlinear Dynamic Behavior of Functional Gradient Viscoelastic Porous Plates
  Year: 2025
  Citations: 1

• Title: Robust Shape Optimization Using Artificial Neural Networks Based Surrogate Modeling for an Aircraft Wing
  Year: 2024
  Citations: 2

Conclusion

Dr. Badr Abou El Majd exemplifies the modern researcher—analytically rigorous, deeply interdisciplinary, and globally connected. With a rich academic background, impactful research portfolio, and broad leadership experience, he stands as a leading figure in applied mathematics and computational engineering. His ability to bridge theoretical models with industrial and societal needs—through projects in aerospace, healthcare, and smart systems—demonstrates both vision and practical utility. Through international collaborations, patents, high-impact publications, and mentorship roles, he continues to shape emerging research frontiers. His blend of technical depth, strategic leadership, and commitment to innovation make him not only a deserving recipient of high research honors but also a catalyst for future scientific and technological advancements in global contexts.