Dr. Ahmed EL HAMDAOUI | Nonlinear Optical Applications | Best Researcher Award

Dr. Ahmed EL HAMDAOUI | University Hassan II of Casablanca | Morocco

Dr. Ahmed EL HAMDAOUI is a researcher in Computational Materials Science and Artificial Intelligence. His expertise lies in molecular dynamics simulations and machine learning for predicting and understanding the structural, mechanical, and vibrational behavior of complex materials, especially silicate and bioactive glasses. He has authored multiple scientific publications and presented his work at major international conferences. Alongside research, he is engaged in academic instruction, teaching undergraduate physics and supervising graduate-level research projects in computational modeling and AI. He also conducts training programs in Python programming, data science, and machine learning for scientific applications. Known for his interdisciplinary approach, Dr. EL HAMDAOUI integrates physics, materials science, and artificial intelligence to develop predictive models that accelerate material design. He is also an active contributor to scientific events and community outreach, helping foster collaboration and innovation in his field. His research continues to make impactful contributions to materials informatics and computational physics.

Profile 

Orcid

Education 

Dr. Ahmed EL HAMDAOUI has a strong academic background in physics and materials science. He completed advanced studies focused on the use of molecular dynamics and machine learning for the analysis of silicate-based materials, contributing to the field of computational materials science. His master’s research involved the application of physics to archaeological dating and materials characterization, while his undergraduate work focused on the comparative performance of solar energy technologies. Throughout his academic journey, he developed a deep understanding of condensed matter physics, simulation tools, and data-driven modeling. He gained experience in handling scientific programming languages and simulation environments that are essential for modern materials research. His education has been multidisciplinary, incorporating theoretical physics, numerical simulation, and real-world applications. This strong academic foundation enables him to explore complex problems in materials science, apply machine learning to physical systems, and supervise research that bridges computational methods and experimental validation.

Experience

Dr. Ahmed EL HAMDAOUI has hands-on experience in both research and teaching within physics and materials science. His research includes the use of molecular dynamics to simulate glassy materials and machine learning techniques to predict mechanical and structural properties. He has studied vibrational anomalies, ion mobility, densification effects, and mechanical behavior in silicate, bioactive, and amorphous materials. As a research supervisor, he has guided graduate projects that explore the intersection of deep learning, molecular modeling, and material property prediction. In teaching, he delivers undergraduate physics courses such as thermodynamics, electromagnetism, and optics, and conducts practical lab sessions in mechanics, electricity, and instrumentation. Additionally, he provides professional training in Python programming and machine learning for scientific research. He also contributes to scientific events and academic outreach, serving on organizing committees and mentoring new students. His professional profile blends scientific rigor, teaching excellence, and applied computational research.

Awards and Honors

Dr. Ahmed EL HAMDAOUI has received recognition for his research contributions through invitations to present at national and international scientific conferences, workshops, and academic forums. His work on vibrational properties in glasses, mechanical property prediction using AI, and structure-property relationships in complex materials has gained visibility in the computational physics and materials science communities. He has played active roles in organizing scientific events, such as doctoral symposiums and research collaboration meetings, contributing to academic life beyond individual research. Participation in high-level international workshops on machine learning in condensed matter physics reflects his selection by leading scientific institutions. His leadership in guiding research projects and training students also reflects trust in his expertise. While his honors are not tied to specific awards, his consistent presence and contributions at influential scientific events and communities demonstrate his growing reputation and impact as a researcher and educator in computational materials science.

Research Focus

Dr. Ahmed EL HAMDAOUI focuses on computational modeling of materials using molecular dynamics simulations and artificial intelligence. His research addresses how atomic-scale structures influence macroscopic properties in glassy and amorphous materials. He explores structural anomalies such as the Boson peak, mechanical properties like Young’s modulus, and the effects of compositional changes and densification. By combining physical simulations with machine learning models, he aims to develop predictive frameworks for materials with tailored properties. His studies extend to perovskites, bioactive glasses, and ion-conducting glasses used in energy and biomedical applications. He also works on understanding ion mobility and structural evolution in multi-component glass systems. His interdisciplinary approach integrates physics, materials science, and data science to uncover hidden relationships and enable intelligent material design. The long-term goal of his research is to accelerate the development of advanced materials through simulation-driven and AI-enhanced methodologies, contributing to fields like renewable energy, nuclear safety, and materials engineering.

Publications 

The boson peak in silicate glasses: insight from molecular dynamics

• Authors: A. El Hamdaoui, E. M. Ghard i, A. Atila, H. Jabraoui, M. Badawi, A. Hasnaoui, S. Ouaskit RSC Publishing+1

• Journal: Physical Chemistry Chemical Physics

• Year: 2023

Young’s Modulus of Calcium‑Alumino‑Silicate Glasses: Insight from Machine Learning

• Authors: Mouna Sbai Idrissi, Ahmed El Hamdaoui, Tarik Chafiq OUCI

• Journal: Journal of Marine Technology and Environment

• Year: 2024

The impact of densification on the boson peak and structure in vitreous silica

• Authors: Ahmed El Hamdaoui, El Mehdi Ghard i, Michael J. D. Rushton, Abdellatif Hasnaoui, Said Ouaskit Bangor University

• Journal: Journal of the American Ceramic Society

• Year : 2025

Conclusion

In summary, Dr. Ahmed EL is a highly capable and impactful researcher whose work bridges fundamental physics, computational modeling, and artificial intelligence. His contributions to understanding and predicting the properties of complex materials demonstrate both scientific depth and interdisciplinary innovation. With ongoing progress in high-impact publications, broader collaborations, and industry engagement, he stands as a strong and deserving candidate for the Research for Best Researcher Award.