Rami Ahmad El-Nabulsi | Nanoscale Photonics Research | Excellence in Innovation Award

Prof. Dr. Rami Ahmad El-Nabulsi | Nanoscale Photonics Research | Excellence in Innovation Award

CESNET | Czech Republic

Prof. Dr. Rami Ahmad El-Nabulsi is a distinguished theoretical physicist and applied mathematician affiliated with CESNET in Prague, the University of South Bohemia in the Czech Republic, and the Center of Excellence in Quantum Technology at Chiang Mai University, Thailand. He holds a Ph.D. in particle and mathematical physics, with a strong foundation in plasma physics and applied mathematics. His interdisciplinary research spans quantum theory, nonlinear dynamics, nanophotonics, solid-state physics, superconductivity, plasma MHD, biophysics, geophysics, nuclear engineering, and space sciences. Widely recognized for his pioneering contributions, he has published extensively in leading international journals and serves on the editorial boards of numerous scientific publications. He is regularly invited to speak at global scientific forums and acts as a reviewer for a broad range of journals. His work combines advanced theoretical modeling with practical applications in cutting-edge fields such as quantum technologies and optical sciences. Prof. Dr. El-Nabulsi has received numerous international honors and awards, and his scholarly influence continues to grow. Alongside his research, he remains dedicated to education and mentorship, shaping future leaders in science and engineering.

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Featured Publications 

  • El-Nabulsi, R. A. (2025). “A model for ice sheets and glaciers in fractal dimensions.” Polar Science.

  • El-Nabulsi, R. A., & Anukool, W. (2025). “Modeling stochastic Langevin dynamics in fractal dimensions.” Physica A: Statistical Mechanics and its Applications.

  • El-Nabulsi, R. A. (2025). “Propagation of nonlinear acoustic fields in thermoviscous porous media.” Journal of Thermal Stresses.

  • El-Nabulsi, R. A., & Anukool, W. (2025). “Qualitative financial modelling in fractal dimensions.” Financial Innovation.

  • El-Nabulsi, R. A., & Anukool, W. (2025). “Structural analysis of phononic crystals and propagation of elastic waves in cubic solids in fractal dimensions.” Journal of Elasticity.

  • El-Nabulsi, R. A., & Anukool, W. (2025, October). “Fractal-based generalization of Pennes’ bioheat transfer equation for hyperthermia applications in cancer therapy.” Thermal Advances.

  • El-Nabulsi, R. A., & Anukool, W. (2025, August 10). “Cosmic transit in phantom massive Chern–Simons models: Confrontations with astronomical observations.” Modern Physics Letters A.

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.

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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.

 

 

PingAn Hu | Light-Matter Interactions | Best Researcher Award

Prof. PingAn Hu | Light-Matter Interactions | Best Researcher Award

Prof. PingAn Hu, Harbin Institute Technology, China

Professor PingAn Hu is a globally recognized materials scientist and innovator in 2D semiconductors, flexible intelligent devices, and neuromorphic vision systems. Currently serving as a Professor at Harbin Institute of Technology (HIT), he is known for groundbreaking work in the interface-engineered growth of large-area single-crystal thin films. With over 240 SCI-indexed publications and accolades including the Elsevier Highly Cited Researcher (2022–2024), his research has gained international recognition and transformed the field of smart sensors and semiconductor technologies.

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📘 Early Academic Pursuits

Prof. Hu began his academic journey with a Ph.D. in Chemistry from the Institute of Chemistry, Chinese Academy of Sciences (2004). His early postdoctoral experiences reflect a rich international academic exposure, serving as a JSPS Fellow at Waseda University, Japan (2004–2006) and a Research Associate at the University of Cambridge, UK (2006–2009). These formative years helped shape his cross-disciplinary research philosophy, integrating material chemistry, surface physics, and device engineering.

🏛️ Professional Endeavors

Upon returning to China, Prof. Hu joined the Harbin Institute of Technology, where he has played a pivotal role in advancing the university’s global reputation in materials science and applied nanotechnology. He currently serves as Editor-in-Chief of the international journal Smart Wearable Technology and is an active member of several academic societies including the China Microelectronics Association, American Carbon Society, and Chinese Society of Nanotechnology.

🔬 Contributions and Research Focus

Prof. Hu’s research addresses some of the most critical challenges in semiconductor device engineering, especially those involving interface sensitivity, optical signal processing, and mechanical-electrical signal transduction. His three core innovations include:

  • Wafer-scale growth of 2D single-crystal materials (like graphene and h-BN) using a liquid copper strategy.

  • Discovery of interlayer-dependent piezoelectric enhancement in van der Waals materials, crucial for next-gen energy devices.

  • Development of low-power neuromorphic vision devices through interface modulation of photocarrier relaxation dynamics, enabling bioinspired and skin-like sensors.

These innovations establish new theoretical foundations for surface/interface-mediated growth and flexible optoelectronic systems, directly impacting fields such as wearable tech, AI-driven sensing, and energy harvesting.

🌍 Impact and Influence

Prof. Hu’s research has not only led to over 240 peer-reviewed publications in top-tier journals (e.g., Nature Communications, Advanced Materials, ACS Nano, Chemical Engineering Journal) but has also been recognized by Nobel Laureates such as Prof. Andre K. Geim and Prof. Konstantin Novoselov. His work is widely cited, contributing to key advances in piezoelectric and neuromorphic research. He maintains active collaborations with over 30 global research institutions, including the University of Cambridge and the University of Michigan, fostering strong international partnerships.

📊 Academic Citations and Metrics

With an extensive body of work cited thousands of times globally, Prof. Hu’s H-index and citation count reflect his authoritative influence in semiconductor materials, nanostructures, and bioinspired electronic systems. Being named a Highly Cited Researcher by Elsevier (2022, 2023, 2024) further substantiates the global reach and reliability of his contributions.

🧠 Research Skills and Interdisciplinary Expertise

Prof. Hu is proficient in a broad range of advanced techniques, including:

  • CVD and epitaxial growth of 2D materials,

  • Piezoelectric and optoelectronic property characterization,

  • Photodetector and tactile sensor engineering,

  • Device simulation and theoretical modeling,

  • Surface/interface modification for neuromorphic functions.

His ability to bridge fundamental research with practical applications makes him a leading voice in interdisciplinary material sciences.

👨‍🏫 Teaching Experience

As a senior faculty member at HIT, Prof. Hu has supervised numerous Ph.D. and postdoctoral researchers, many of whom now hold academic and industrial positions worldwide. His courses on nanomaterials, advanced electronic devices, and flexible electronics are considered core components of the institute’s postgraduate curriculum. He is also involved in talent training through China’s National Talent Programs.

🏆 Awards and Honors

  • Elsevier Highly Cited Researcher (2022–2024)

  • First Prize, Science and Technology Award (2015, 2020 – Principal Investigator)

  • Second Prize, Science and Technology Award (2024 – Third Contributor)

  • Editor-in-Chief, Smart Wearable Technology (International Journal)

  • 21 authorized invention patents in flexible electronics, sensors, and 2D materials.

These awards reflect his sustained excellence, innovation, and leadership across academia and applied research.

🔮 Legacy and Future Contributions

Looking ahead, Prof. Hu aims to advance AI-integrated sensor systems, energy-autonomous wearables, and interface-programmable devices for next-generation applications in healthcare, soft robotics, and environmental monitoring. His vision includes creating eco-friendly, bioinspired smart systems and globalizing knowledge transfer through deeper international collaborations and industrial translation of lab breakthroughs.

Top Publications

Prestrain Guided Yield of Large Single-Crystal Nickel Foils, with High-Index Facets

  • Authors: Zhen Su, Meixiu Song, Huyang Li, Xin Song, Yuming Feng, Shuai Wang, Xin Zhang, Hongying Yang, Xingji Li, Yanxiang Zhang, Yuhang Jing, PingAn Hu
    Journal: Advanced Materials
    Year: 2024

Flexible Optical Synapses Based on In₂Se₃/MoS₂ Heterojunctions for Artificial Vision Systems in the Near-Infrared Range

  • Authors: Hu YX, Yang HY, (…) Hu PA
    Journal: ACS Applied Materials & Interfaces
    Year: 2022

Engineering the Optoelectronic Properties of 2D Hexagonal Boron Nitride Monolayer Films by Sulfur Substitutional Doping

  • Authors: Biying Tan, You Wu, Feng Gao, Huihui Yang, Yunxia Hu, Huiming Shang, Xin Zhang, Jia Zhang, Zhonghua Li, YongQing Fu, PingAn Hu
    Journal: ACS Applied Materials & Interfaces
    Year: 2022

Skin-Inspired Tactile Sensor Based on Gradient Pore Structure Enables Broad Range Response and Ultrahigh Pressure Resolution

  • Authors: S. Wang, F. Gao, Y. Hu, S. Zhang, H. Shang, C. Ge, B. Tan, X. Zhang, J. Zhang, P. Hu
    Journal: Chemical Engineering Journal
    Year: 2022

Field Effect Transistor Sensors Based on In-Plane 1T′/2H/1T′ MoTe₂ Heterophases with Superior Sensitivity and Output Signals

  • Authors: Shichao Zhang, You Wu, Feng Gao, Huiming Shang, Jia Zhang, Zhonghua Li, YongQing Fu, PingAn Hu
    Journal: Advanced Functional Materials
    Year: 2022