Ahmed EL HAMDAOUI | Nonlinear Optical Applications | Best Researcher Award

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 

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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.

 

 

Guangwen Li | Imaging Technology Development | Clinical Research Award

Prof. Dr. Guangwen Li | Imaging Technology Development | Clinical Research Award

Prof. Dr. Guangwen Li,The Affiliated Hospital of Qingdao University, China 

Dr. Guangwen Li is the Chief of the Neurology Department at The Affiliated Hospital of Qingdao University, where he leads with distinction in both clinical care and translational neuroscience research. Holding an MD and PhD, Dr. Li has built an exemplary career focused on the basic and clinical study of cerebrovascular diseases, with over 58 publications, 5 published books, and 2 patents to his credit. He is recognized not only as a researcher but also as an academic leader and thought partner in stroke and neurovascular care.

Profile

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🎓 Early Academic Pursuits

Dr. Li’s journey in medicine began with a rigorous academic foundation, culminating in a PhD in Neurology, where he focused on vascular pathology and brain repair mechanisms. From his early years, he demonstrated a strong interest in stroke research, particularly mechanisms underlying ischemic injury and recovery, which laid the groundwork for his future scientific inquiries.

🧑‍💼 Professional Endeavors

In his current role as Chief of Neurology, Dr. Li is not only a clinician but also a dedicated academic. He oversees clinical neurology services, mentors early-career researchers, and directs multi-disciplinary stroke research projects. His active roles as Associate Editor and Editorial Board Member across journals like Frontiers in Neuroscience, JNIS, and Clinical Neuroscience Research reflect his broad influence in scientific publishing and peer review.

🧠 Contributions and Research Focus

Dr. Li’s research primarily explores ischemic stroke, with special attention to the neuroinflammatory response, non-coding RNAs, and endovascular intervention timing. His landmark contributions include:

  • Exploring the role of neutrophil-mediated inflammatory pathways in stroke pathology.

  • Defining the optimal therapeutic window for endovascular treatment in intracranial atherosclerotic stenosis.

  • Investigating the lncRNA H19/miRNA-29b axis and its effect on the blood-brain barrier in stroke.
    These studies position him at the forefront of neurovascular medicine and post-stroke neurorepair.

🌍 Impact and Influence

With 58 peer-reviewed publications indexed in SCI and Scopus, a citation index of 28, and key involvement in five major research projects, Dr. Li’s work is steadily shaping the direction of modern stroke therapy and translational neurobiology. His role in multiple collaborative projects underscores his commitment to interdisciplinary and cross-institutional research.

📊 Academic Citations

Although currently holding a citation index of 28, Dr. Li’s publication rate and the emerging relevance of his research areas suggest that his academic influence is on a rising trajectory. His novel insights into neuroprotection and gene regulation in stroke have the potential for greater international citation and recognition in the coming years.

🧪 Research Skills

Dr. Li is proficient in a range of molecular, cellular, and translational neuroscience techniques, including:

  • lncRNA and miRNA functional analysis

  • Stroke modeling in vivo

  • Endovascular procedural studies

  • Exosomal biomarker research
    His research showcases a strong integration of laboratory science with clinical application, making his approach highly translational and impactful.

👨‍🏫 Teaching Experience

In addition to his clinical and research leadership, Dr. Li is an active educator, mentoring residents, PhD candidates, and junior faculty in clinical neurology, stroke management, and research methodology. His involvement in curriculum development and neurology training programs adds further value to his institution and students.

🏅 Awards and Honors

While specific honors are not listed, Dr. Li’s editorial appointments, professional memberships, and selection to elite research boards—such as Neural Regeneration Research and Frontiers in Neurology—highlight his academic recognition and leadership stature in the neuroscience community.

🔬 Legacy and Future Contributions

Dr. Guangwen Li is poised to leave a lasting legacy in stroke care and neurovascular research. His future goals likely include:

  • Expanding international collaborations

  • Translating bench findings into bedside therapies

  • Developing precision medicine approaches for stroke rehabilitation
    With his current momentum, Dr. Li is well-positioned to influence policy, clinical protocols, and medical education in neurology on a global scale.

Publications 

  •  Submaximal versus aggressive angioplasty with drug-coated balloons for symptomatic intracranial arterial stenosis
    Authors: Guangwen Li, Yayue Liu, Xiaofei Sun, Yujie Sun, Peng Liu, Xianjun Zhang, Xie Anmu, Yong Zhang
    Journal: Journal of NeuroInterventional Surgery
    Year: 2025

  • Has collateral blood flow any effect on restenosis rate? Our experience
    Authors: Li Y, Sun Y, Liu T, Liu P, Li G, Zhang Y
    Journal: Frontiers in Neurology
    Year: 2024

  • Predictive factors of poor outcome and mortality among anterior ischaemic stroke patients despite successful recanalisation in China: a secondary analysis of the CAPTURE trial
    Authors: Guangwen Li, Yujie Sun, Tonghui Liu, Pengfei Yang, Ya Peng, Wenhuo Chen, Liyong Zhang, Jianfeng Chu, Dong Kuai, Zibo Wang et al.
    Journal: BMJ Open
    Year: 2023

  • MicroRNA-29b Suppresses Inflammation and Protects Blood-Brain Barrier Integrity in Ischemic Stroke
    Authors: Xiaoqing Ma, Ho Jun Yun, Kenneth Elkin, Yunlneuroprotectioniang Guo, Yuchuan Ding, Guangwen Li, Feng Zhang
    Journal: Mediators of Inflammation
    Year: 2022

  • MicroRNA-193a-5p Rescues Ischemic Cerebral Injury by Restoring N2-Like Neutrophil Subsets
    Authors: Han Z, Li L, Zhao H, Xiaogang Wang, Yan F, Tao Z, Fan J, Zheng Y, Zhao F, Huang Y et al.
    Journal: Translational Stroke Research
    Year: 2022